Methods and systems for genetic analysis

ABSTRACT

This disclosure provides systems and methods for sample processing and data analysis. Sample processing may include nucleic acid sample processing and subsequent sequencing. Some or all of a nucleic acid sample may be sequenced to provide sequence information, which may be stored or otherwise maintained in an electronic storage location. The sequence information may be analyzed with the aid of a computer processor, and the analyzed sequence information may be stored in an electronic storage location that may include a pool or collection of sequence information and analyzed sequence information generated from the nucleic acid sample. Methods and systems of the present disclosure can be used, for example, for the analysis of a nucleic acid sample, for producing one or more libraries, and for producing biomedical reports. Methods and systems of the disclosure can aid in the diagnosis, monitoring, treatment, and prevention of one or more diseases and conditions.

CROSS-REFERENCE

This application is a divisional application of U.S. patent applicationSer. No. 17/080,474, filed Oct. 26, 2020, which is a continuationapplication of U.S. patent application Ser. No. 16/816,135, filed Mar.11, 2020, which is a continuation application of U.S. patent applicationSer. No. 16/526,928, filed Jul. 30, 2019, which is a continuationapplication of U.S. patent application Ser. No. 15/996,215, filed Jun.1, 2018, now U.S. Pat. No. 10,415,091, which is a continuationapplication of U.S. patent application Ser. No. 14/810,337, filed Jul.27, 2015, now U.S. Pat. No. 10,266,890, which is a divisionalapplication of U.S. patent application Ser. No. 14/141,990, filed Dec.27, 2013, now U.S. Pat. No. 9,128,861, which claims priority to U.S.Provisional Application No. 61/753,828, filed Jan. 17, 2013, each ofwhich is incorporated herein by reference in its entirety.

BACKGROUND

Current methods for whole genome and/or exome sequencing may be costlyand fail to capture many biomedically important variants. For example,commercially available exome enrichment kits (e.g., Illumina's TruSeqexome enrichment and Agilent's SureSelect exome enrichment), may fail totarget biomedically interesting non-exomic and exomic regions. Often,whole genome and/or exome sequencing using standard sequencing methodsperforms poorly in content regions having very high CG content (>70%).Furthermore, whole genome and/or exome sequencing also fail to provideadequate and/or cost-effective sequencing of repetitive elements in thegenome.

The methods disclosed herein provide specialized sequencing protocols ortechnologies to address these issues.

SUMMARY

Provided herein is a method for analyzing a nucleic acid sample,comprising (a) producing two or more subsets of nucleic acid moleculesfrom a nucleic acid sample, wherein (i) the two or more subsets comprisea first subset of nucleic acid molecules and a second subset of nucleicacid molecules, and (ii) the first subset of nucleic acid moleculesdiffers from the second subset of nucleic acid molecules by one or morefeatures selected from genomic regions, mean GC content, mean molecularsize, subset preparation method, or combination thereof; (b) conductingone or more assays on at least two of the two or more subsets of nucleicacid molecules, wherein (i) a first assay, comprising a first sequencingreaction, is conducted on the first subset of the two or more subsets toproduce a first result, and (ii) a second assay is conducted on thesecond subset of the two or more subsets to produce a second result; and(c) combining, with the aid of a computer processor, the first resultand second result, thereby analyzing the nucleic acid sample.

Also provided herein is a method for analyzing a nucleic acid sample,comprising (a) producing two or more subsets of nucleic acid moleculesfrom a nucleic acid sample, wherein the two or more subsets differ byone or more features selected from genomic regions, mean GC content,mean molecular size, subset preparation method, or combination thereof;(b) combining at least two of the two or more subsets of nucleic acidmolecules to produce a first combined pool of nucleic acid molecules;and (c) conducting one or more assays on the first combined pool ofnucleic acid molecules, wherein at least one of the one or more assayscomprises a sequencing reaction.

Disclosed herein is a method for analyzing a nucleic acid sample,comprising (a) producing two or more nucleic acid molecules subsets froma nucleic acid sample, wherein producing the two or more nucleic acidmolecules comprise enriching the two or more subsets of nucleic acidmolecules for two or more different genomic regions; (b) conducting afirst assay on a first subset of nucleic acid molecules among the two ormore subsets of nucleic acid molecules to produce a first result,wherein the first assay comprises a first sequencing reaction; (c)conducting a second assay on at least a second subset of nucleic acidmolecules among the two or more subsets of nucleic acid molecules toproduce a second result; and (d) combining, with the aid of a computerprocessor, the first result with the second result, thereby analyzingthe nucleic acid sample.

Further provided herein is a method for analyzing a nucleic acid sample,comprising (a) preparing at least a first subset of nucleic acidmolecules and a second subset of nucleic acid molecules from a nucleicacid sample, wherein the first subset of nucleic acid molecules differsfrom the second subset of nucleic acid molecules; (b) conducting a firstassay on the first subset of nucleic acid molecules and a second assayon the second subset of nucleic acid molecules, wherein the first assaycomprises a nucleic acid sequencing reaction that produces a firstresult, comprising nucleic acid sequence information for the firstsubset, and wherein the second assay produces a second result; (c)analyzing, with the aid of a computer processor, the first result toprovide a first analyzed result and analyzing the second result toprovide a second analyzed result; and (d) combining, with the aid of acomputer processor, the first and second analyzed results, therebyanalyzing the nucleic acid sample.

Provided herein is a method for analyzing a nucleic acid, comprising (a)producing one or more subsets of nucleic acid molecules from a nucleicacid sample, wherein producing the one or more subsets of nucleic acidmolecules comprises conducting a first assay in the presence of one ormore antioxidants to produce a first subset of nucleic acid molecules;and (b) conducting a sequencing reaction on the one or more subsets ofnucleic acid molecules, thereby analyzing the nucleic acid sample.

Also disclosed herein is a method for analyzing a nucleic acid sample,comprising (a) producing, with the aid of a computer processor, one ormore capture probes, wherein the one or more capture probes hybridize toone or more polymorphisms, wherein the one or more polymorphisms arebased on or extracted from one or more databases of polymorphisms,observed in a population of one or more samples, or a combinationthereof; (b) contacting a nucleic acid sample with the one or morecapture probes to produce one or more capture probe hybridized nucleicacid molecules; and (c) conducting a first assay on the one or morecapture probe hybridized nucleic acid molecules, thereby analyzing thenucleic acid sample, wherein the first assay comprises a sequencingreaction.

Further disclosed herein is a method for developing complementarynucleic acid libraries, comprising (a) producing two or more subsets ofnucleic acid molecules from a sample, wherein (i) the two or moresubsets of nucleic acid molecules comprise a first subset of nucleicacid molecules and a second subset of nucleic acid molecules, (ii) thefirst subset of nucleic acid molecules comprises nucleic acid moleculesof a first mean size, (iii) the second subset of nucleic acid moleculescomprises nucleic acid molecules of a second mean size, and (iv) thefirst mean size of the first subset of nucleic acid molecules is greaterthan the second mean size of the second subset of nucleic acid moleculesby about 200 or more residues; (b) producing two or more nucleic acidlibraries, wherein (i) the two or more libraries comprise a firstnucleic acid molecules library and second nucleic acid moleculeslibrary, (ii) the first nucleic acid molecules library comprises the oneor more nucleic acid molecules from the first subset of nucleic acidmolecules, (iii) the second nucleic acid molecules library comprises theone or more nucleic acid molecules from the second subset of nucleicacid molecules, and (iv) the content of the first nucleic acid moleculeslibrary is at least partially complementary to the content of the secondnucleic acid molecules library.

Provided herein is a method for developing complementary nucleic acidlibraries, comprising (a) producing two or more subsets of nucleic acidmolecules from a sample of nucleic acid molecules, wherein the two ormore subsets of nucleic acid molecules comprise a first subset ofnucleic acid molecules and a second subset of nucleic acid molecules;(b) conducting two or more assays on the two or more subsets of nucleicacid molecules, wherein (i) the two or more assays comprise a firstassay and a second assay, (ii) the first assay comprises conducting afirst amplification reaction on the first subset of nucleic acidmolecules to produce one or more first amplified nucleic acid moleculeswith a first mean GC content, (iii) the second assay comprisesconducting a second amplification reaction on the second subset ofnucleic acid molecules to produce one or more second amplified nucleicacid molecules with a second mean GC content, and (iv) the first mean GCcontent of the first subset of nucleic acid molecules differs from thesecond mean GC content of the second subset of nucleic acid molecules;and (b) producing two or more nucleic acid libraries, wherein (i) thetwo or more libraries comprise a first nucleic acid molecules libraryand second nucleic acid molecules library, (ii) the first nucleic acidmolecules library comprises the one or more first amplified nucleic acidmolecules, (iii) the second nucleic acid molecules library comprises theone or more second amplified nucleic acid molecules, and (iv) thecontent of the first nucleic acid molecules library is at leastpartially complementary to the content of the second nucleic acidmolecules library.

Also provided herein is a method for developing complementary nucleicacid libraries, comprising (a) producing two or more subsets of nucleicacid molecules from a sample of nucleic acid molecules, wherein (i) thetwo or more subsets of nucleic acid molecules comprise a first subset ofnucleic acid molecules and a second subset of nucleic acid molecules,and (ii) the two or more subsets of nucleic acid molecules differ by oneor more features selected from genomic regions, mean GC content, meanmolecular size, subset preparation method, or combination thereof; and(b) producing two or more nucleic acid libraries, wherein (i) the two ormore libraries comprise a first nucleic acid molecules library andsecond nucleic acid molecules library, (ii) the first nucleic acidmolecules library comprises the one or more nucleic acid molecules fromthe first subset of nucleic acid molecules, (iii) the second nucleicacid molecules library comprises the one or more nucleic acid moleculesfrom the second subset of nucleic acid molecules, and (iv) the contentof the first nucleic acid molecules library is at least partiallycomplementary to the content of the second nucleic acid moleculeslibrary.

Disclosed herein is a method for sequencing, comprising (a) contacting anucleic acid sample with one or more capture probe libraries to produceone or more capture probe hybridized nucleic acid molecules; and (b)conducting one or more sequencing reactions on the one or more captureprobe hybridized nucleic acid molecules to produce one or more sequencereads, wherein (i) the sensitivity of the sequencing reaction isimproved by at least about 4% as compared current sequencing methods;(ii) the sensitivity of the sequencing reaction for a genomic regioncomprising a RefSeq is at least about 85%, (iii) the sensitivity of thesequencing reaction for a genomic region comprising an interpretablegenome is at least about 88%, (iv) the sensitivity of the sequencingreaction for an interpretable variant is at least about 90%, or (v) acombination of (i)-(ii).

At least one of the one or more capture probe libraries may comprise oneor more capture probes to one or more genomic regions.

The methods and systems disclosed herein may further comprise conductingone or more sequencing reactions on one or more capture probe freenucleic acid molecules.

The percent error of the one or more sequencing reactions may similar tocurrent sequencing methods. The percent error rate of the one or moresequencing reactions may be within about 0.001%, 0.002%, 0.003%, 0.004%,0.005%, 0.006%, 0.007%, 0.008%, 0.009%, 0.01%, 0.02%, 0.03%, 0.04%,0.05%, 0.06%, 0.07%, 0.08%, 0.09%, 1%, 1.1%, 1.2%, 1.3%, 1.4%, 1.5%,1.6%, 1.7%, 1.8%, 1.9%, or 2% of the current sequencing methods. Thepercent error of the one or more sequencing reactions is less than theerror rate of current sequencing methods. The percent error of thesequencing reaction may be less than about 1.5%, 1%, 0.75%, 0.50%,0.25%, 0.10%, 0.075%, 0.050%, 0.025%, or 0.001%.

The accuracy of the one or more sequencing reactions may similar tocurrent sequencing methods. The accuracy of the one or more sequencingreactions is better than current sequencing methods.

The nucleic acid molecules may be DNA. The nucleic acid molecules may beRNA.

The methods and systems may comprise a second subset of nucleic acidmolecules. The first subset and the second subset of nucleic acidmolecules may differ by one or more features selected from genomicregions, mean GC content, mean molecular size, subset preparationmethod, or combination thereof.

The one or more genomic regions may be selected from the groupcomprising high GC content, low GC content, low complexity, lowmappability, known single nucleotide variations (SNVs), known inDels,known alternative sequences, entire genome, entire exome, set of genes,set of regulatory elements, and methylation state.

The set of genes may selected from a group comprising set of genes withknown Mendelian traits, set of genes with known disease traits, set ofgenes with known drug traits, and set of genes with known biomedicallyinterpretable variants.

The known alternative sequences may be selected from the groupcomprising one or more small insertions, small deletions, structuralvariant junctions, variable length tandem repeats, and flankingsequences.

The subsets of nucleic acid molecules may differ by mean molecular size.The difference in mean molecular size between at least two of thesubsets of nucleic acid molecules is at least 100 nucleotides. Thedifference in mean molecular size between at least two of the subsets ofnucleic acid molecules is at least 200 nucleotides. The difference inmean molecular size between at least two of the subsets of nucleic acidmolecules is at least 300 nucleotides.

The subsets of nucleic acid molecules may differ by mean GC content. Themean GC content of one or more subsets may be greater than or equal to70%. Alternatively, the mean GC content of one or more subsets may beless than 70%. The difference between the mean GC content of two or moresubsets may be at least about 5%, 10%, 15% or more.

One or more additional assays may be conducted. A second assay may beconducted. A third assay may be conducted. A fourth assay may beconducted. A fifth, sixth, seventh, eighth, ninth, or tenth assay may beconducted. The one or more assays may comprise one or more sequencingreactions, amplification reactions, hybridization reactions, detectionreaction, enrichment reactions, or a combination thereof.

The one or more assays may produce one or more results. The second assaymay comprise a nucleic acid sequencing reaction that produces the secondresult, and wherein the second result may comprise nucleic acid sequenceinformation for the second subset.

The first and second assays may be conducted separately. The first andsecond assays may be conducted sequentially. The first and second assaysmay be conducted simultaneously.

At least two of the subsets of nucleic acid molecules may be combined toproduce a combined subset of nucleic acid molecules. The first andsecond assays may be conducted on the combined subset of nucleic acidmolecules.

The first assay and the second assay may be the same. The first assayand the second assay may be different.

Analyzing the nucleic acid sample may comprise producing a unifiedassessment of the sample genetic state at each locus addressed by theassays.

Conducting one or more amplification reactions may comprise one or morePCR-based amplifications, non-PCR based amplifications, or a combinationthereof. The one or more PCR-based amplifications may comprise PCR,qPCR, nested PCR, linear amplification, or a combination thereof. Theone or more non-PCR based amplifications may comprise multipledisplacement amplification (MDA), transcription-mediated amplification(TMA), nucleic acid sequence-based amplification (NASBA), stranddisplacement amplification (SDA), real-time SDA, rolling circleamplification, circle-to-circle amplification or a combination thereof.

The sequencing reactions may comprise capillary sequencing, nextgeneration sequencing, Sanger sequencing, sequencing by synthesis,single molecule nanopore sequencing, sequencing by ligation, sequencingby hybridization, sequencing by nanopore current restriction, or acombination thereof. Sequencing by synthesis may comprise reversibleterminator sequencing, processive single molecule sequencing, sequentialnucleotide flow sequencing, or a combination thereof. Sequentialnucleotide flow sequencing may comprise pyrosequencing, pH-mediatedsequencing, semiconductor sequencing or a combination thereof.Conducting one or more sequencing reactions comprises whole genomesequencing or exome sequencing.

The sequencing reactions may comprise one or more capture probes orlibraries of capture probes. At least one of the one or more captureprobe libraries may comprise one or more capture probes to 1, 2, 3, 4,5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or more genomic regions. Thelibraries of capture probes may be at least partially complementary. Thelibraries of capture probes may be fully complementary. The libraries ofcapture probes may be at least about 5%, 10%, 15%, 20%, %, 25%, 30%,35%, 40%, 45%, 50%, 55%, 60%, 70%, 80%, 90%, 95%, 97% or morecomplementary.

The methods and systems disclosed herein may further comprise conductingone or more sequencing reactions on one or more capture probe freenucleic acid molecules. The methods and systems disclosed herein mayfurther comprise conducting one or more sequencing reactions on one ormore subsets on nucleic acid molecules comprising one or more captureprobe free nucleic acid molecules.

The methods and systems disclosed herein may increase the sensitivity ofone or more sequencing reactions when compared to the sensitivity ofcurrent sequencing methods. The sensitivity of the one or moresequencing reactions may increase by at least about 1%, 2%, 3%, 4%, 5%,5.5%, 6%, 6.5%, 7%, 7.5%, 8%, 8.5%, 9%, 9.5%, 10%, 10.5%, 11%, 12%, 13%,14%, 15%, 16%, 17%, 18%, 19%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%,60%, 70%, 80%, 90%, 95%, 97% or more. The sensitivity of the one or moresequencing reactions may increase by at least about 4.5-20%, about5-15%, about 7%-12%, or about 8%-10%.

The percent error of the one or more sequencing reactions may similar tocurrent sequencing methods. The percent error rate of the one or moresequencing reactions may be within about 0.001%, 0.002%, 0.003%, 0.004%,0.005%, 0.006%, 0.007%, 0.008%, 0.009%, 0.01%, 0.02%, 0.03%, 0.04%,0.05%, 0.06%, 0.07%, 0.08%, 0.09%, 1%, 1.1%, 1.2%, 1.3%, 1.4%, 1.5%,1.6%, 1.7%, 1.8%, 1.9%, or 2% of the current sequencing methods. Thepercent error rate of the one or more sequencing reactions may be lessthan the percent error rate of current sequencing methods. The percenterror rate of the one or more sequencing reactions may be at least about10%, 9,%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1.75%, 1.5%, 1.25%, 1%, 0.9%,0.8%, 0.7%, 0.6%, 0.5%, 0.4%, 0.3%, 0.2%, 0.1% less than the percenterror rate of current sequencing methods. The percent error rate of thesequencing reaction may be less than about 2%, 1.75%, 1.5%, 1.25%, 1%,0.75%, 0.50%, 0.25%, 0.10%, 0.075%, 0.050%, 0.025%, or 0.001%.

The error of the sequencing reactions can be determined as a Phredquality score. The Phred quality score may be assigned to each base callin automated sequencer traces and may be used to compare the efficacy ofdifferent sequencing methods. The Phred quality score (Q) may be definedas a property which is logarithmically related to the base-calling errorprobabilities (P). The Phred quality score (Q) may be calculated asQ=−10 log₁₀P. The Phred quality score of the one or more sequencingreactions may be similar to the Phred quality score of currentsequencing methods. The Phred quality score of the one or moresequencing methods may be within 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 of thePhred quality score of the current sequencing methods. The Phred qualityscore of the one or more sequencing methods may be less than the Phredquality score of the one or more sequencing methods. The Phred qualityscore of the one or more sequencing methods may be at least about 10, 9,8, 7, 6, 5, 4, 3, 2, 1 less than the Phred quality score of the one ormore sequencing methods. The Phred quality score of the one or moresequencing methods may be greater than 5, 6, 7, 8, 9, 10, 11, 12, 13,14, 15, 16, 17, 18, 19, 20, 25, or 30. The Phred quality score of theone or more sequencing methods may be greater than 35, 40, 41, 42, 43,44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, or 60.The Phred quality score of the one or more sequencing methods may be atleast 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50,51, 52, 53, 54, 55, 56, 57, 58, 59, 60 or more.

The accuracy of the one or more sequencing reactions may be similar tocurrent sequencing methods. The accuracy of the one or more sequencingreactions may be within about 0.001%, 0.002%, 0.003%, 0.004%, 0.005%,0.006%, 0.007%, 0.008%, 0.009%, 0.01%, 0.02%, 0.03%, 0.04%, 0.05%,0.06%, 0.07%, 0.08%, 0.09%, 1%, 1.1%, 1.2%, 1.3%, 1.4%, 1.5%, 1.6%,1.7%, 1.8%, 1.9%, 2%, 2.25%, 2.5%, 2.75%, 3%, 3.25%, 3.5%, 3.75%, or 4%of the current sequencing methods. The accuracy of the one or moresequencing reactions may be greater than the accuracy of currentsequencing methods. The accuracy of the one or more sequencing reactionsmay be at least about 0.001%, 0.002%, 0.003%, 0.004%, 0.005%, 0.006%,0.007%, 0.008%, 0.009%, 0.01%, 0.02%, 0.03%, 0.04%, 0.05%, 0.06%, 0.07%,0.08%, 0.09%, 1%, 1.1%, 1.2%, 1.3%, 1.4%, 1.5%, 1.6%, 1.7%, 1.8%, 1.9%,2%, 2.25%, 2.5%, 2.75%, 3%, 3.25%, 3.5%, 3.75%, 4%, 4.5%, 5%, 6%, 7%,8%, 9%, 10%, 11%, 12%, 15%, 17%, 20%, 25%, 30%, 35%, 40%, 50%, or 60%greater than the accuracy of current sequencing methods. The accuracy ofthe sequencing reaction may be greater than about 70%, 75%, 80%, 85%,90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98.25%, 98.5%, 98.75%, 99%,99.25%, 99.5%, or 99.75%. The accuracy of the sequencing reaction may begreater than about 99.1%, 99.2%, 99.3%, 99.4%, 99.5%, 99.6%, 99.7%,99.8%, 99.9%, 99.99%, or 90.999%.

Conducting a detection reaction may comprise optical sensing, electricalsensing, pH sensing, or a combination thereof. Optical sensing maycomprise optical sensing of a photoluminescence photon emission,fluorescence photon emission, pyrophosphate photon emission,chemiluminescence photon emission, or a combination thereof. Electricalsensing may comprise electrical sensing of an ion concentration, ioncurrent modulation, nucleotide electrical fields, nucleotide tunnelingcurrent, or a combination thereof.

Producing the subsets of nucleic acid molecules may comprise conductingan enrichment reaction.

Conducting an enrichment reaction may comprise conducting one or morehybridization reactions. Conducting an enrichment reaction may comprisedifferential amplification of two or more subsets based on one or moregenomic region features.

One or more hybridization reactions may comprise one or morehybridization arrays, hybridization reactions, hybridization chainreactions, isothermal hybridization reactions, nucleic acidhybridization reactions, or a combination thereof. One or morehybridization arrays may comprise hybridization array genotyping,hybridization array proportional sensing, DNA hybridization arrays,macroarrays, microarrays, high-density oligonucleotide arrays, genomichybridization arrays, comparative hybridization arrays, or a combinationthereof. One or more hybridization reactions may comprise a firsthybridization reaction on the first subset of nucleic acid molecules toproduce one or more first hybridized nucleic acid molecules, conductinga second hybridization reaction on the second subset of nucleic acidmolecules to produce one or more second hybridized nucleic acidmolecules, or a combination thereof.

One or more hybridization reactions may comprise one or more sets ofcapture probes. One or more hybridization reactions may comprise (a) afirst subset of nucleic acid molecules comprising one or more captureprobe hybridized nucleic acid molecules; and (b) a second subset ofnucleic acid molecules comprising one or more capture probe free nucleicacid molecules.

One or more or more hybridization reactions may comprise one or moresets of beads. One or more or more sets of beads may comprise (a) afirst subset of nucleic acid molecules comprising one or more bead boundnucleic acid molecules; and (b) a second subset of nucleic acidmolecules comprising one or more bead free nucleic acid molecules.

The methods and systems disclosed herein may further comprise combiningthe results from two or more assays. The methods and systems disclosedherein may further comprise combining the subsets of nucleic acidmolecules after producing two or more subsets of nucleic acid moleculesto produce one or more combined subsets of nucleic acid molecules. Themethods and systems disclosed herein may further comprise combining thesubsets of nucleic acid molecules prior to conducting one or more assaysto produce one or more combined subsets of nucleic acid molecules.Combining the results may comprise combining two or more sequencing datasets by means of a precedence rule utilizing one or more of genomiccontexts and/or assay technology to resolve discordances between two ormore sequencing data sets. Combining the results may comprise combiningtwo or variant call sets by means of a statistical algorithm utilizingone or more of quality and read coverage metrics to resolve one or morediscordant genotypes. Combining the results may comprise combining twoor more assay read data sets by means of a statistical algorithmutilizing one or more of base read quality and allele frequency tocompute a consensus call at one or more applicable loci.

At least two of the subsets of nucleic acid molecules may be fluidicallyseparated. At least two of the subsets of nucleic acid molecules may beseparated into two or more different containers. The two or moredifferent containers may comprise plates, microplates, PCR plates,wells, microwells, tubes, Eppendorf tubes, vials, arrays, microarrays,chips or a combination thereof.

The methods and systems disclosed herein may further comprise producingone or more outputs based on the analysis of the nucleic acid sample.The one or more outputs may comprise one or more biomedical reports. Theone or more biomedical reports may comprise biomedical information of asubject. The biomedical information of the subject predicts, prognoses,or diagnoses one or more biomedical features selected from the group,comprising disease state, genetic risk of a disease, reproductive risk,genetic risk to a fetus, risk of an adverse drug reaction, efficacy of adrug therapy, prediction of optimal drug dosage, transplant tolerance,or a combination thereof.

The methods and systems disclosed herein may further compriseaggregating information from two or more databases. The methods andsystems disclosed herein may further comprise combining information fromtwo or more databases. The databases may comprise biomedical orscientific information. The information may comprise information on oneor more polymorphisms, diseases or conditions, genetic diseases, genes,exomes, genomes, or a combination thereof.

The one or more polymorphisms may comprise one or more insertions,deletions, structural variant junctions, variable length tandem repeats,single nucleotide mutations, or a combination thereof.

The analysis of one or more nucleic sample of (a) and/or the analysis ofone or more nucleic sample of (c) may comprise generating data orresults based on or derived from the analysis of two or more subsets ofnucleic acid molecules.

Disclosed herein is a system comprising (a) first computer processor forproducing a first biomedical report, wherein (i) the first biomedicalreport is generated from data or results based on the analysis of two ormore subsets of nucleic acid molecules from a nucleic acid sample, and(ii) the two or more subsets of nucleic acid molecules differ by one ormore features; (b) a second computer processor for transmitting thefirst biomedical report to a user; (c) a third computer processor forproducing a second biomedical report, wherein (i) the second biomedicalreport is generated from the data or results based on the analysis oftwo or more subsets of nucleic acid molecules from the nucleic acidsample, (ii) the two or more subsets of nucleic acid molecules differ byone or more features, and (iii) the first biomedical report and thesecond biomedical report differ by one or more biomedical features; and(d) a fourth computer processor for transmitting the second biomedicalreport to the user.

Disclosed herein is a system comprising (a) first computer processor forproducing a first biomedical report, wherein the first biomedical reportis generated from data or results based on the analysis of one or morenucleic acid samples; (b) a second computer processor for transmittingthe first biomedical report to a user; (c) a third computer processorfor producing a second biomedical report, wherein (i) the secondbiomedical report is based on or derived from the first biomedicalreport, (ii) the second biomedical report is generated from data orresults based on the analysis of one or more nucleic acid samples, or(iii) a combination of (i)-(ii); and (d) a fourth computer processor fortransmitting the second biomedical report to the user. Analysis of oneor more nucleic sample of (a) and/or the analysis of one or more nucleicsample of (c) may comprise generating data or results based on orderived from the analysis of two or more subsets of nucleic acidmolecules. Transmitting the second biomedical report is based on theanalysis of the first biomedical report.

Further disclosed herein is a system comprising (a) a first computerprocessor for producing a first biomedical report, wherein the firstbiomedical report is generated from data or results based on theanalysis of one or more nucleic acid samples; (b) a second computerprocessor for analyzing the first biomedical report; and (c) a thirdcomputer processor for transmitting a second biomedical report, wherein(i) the second biomedical report is based on or derived from the firstbiomedical report, (ii) the second biomedical report is generated fromdata or results based on the analysis of one or more nucleic acidsamples, or (iii) a combination of (i)-(ii). Analysis of one or morenucleic sample of (a) and/or the analysis of one or more nucleic sampleof (c) may comprise generating data or results based on or derived fromthe analysis of two or more subsets of nucleic acid molecules.

Disclosed herein is a method for generating a biomedical report,comprising (a) receiving, from a user, a first request for a firstbiomedical report, wherein (i) the first biomedical report is generatedfrom data or results based on the analysis of two or more subsets ofnucleic acid molecules from a nucleic acid sample, and (ii) the two ormore subsets of nucleic acid molecules differ by one or more featuresselected from genomic regions, mean GC content, mean molecular size,subset preparation method, or combination thereof; (b) transmitting thefirst biomedical report to the user; (c) receiving, from the user, asecond request for a second biomedical report, wherein (i) the secondbiomedical report is generated from the data or results based on theanalysis of two or more subsets of nucleic acid molecules from thenucleic acid sample, (ii) the two or more subsets of nucleic acidmolecules differ by one or more features, and (iii) the first biomedicalreport and the second biomedical report differ by one or more biomedicalfeatures; and (c) transmitting the second biomedical report to the user.

Disclosed herein is a method for generating a biomedical report,comprising (a) receiving, from a user, a first request for a firstbiomedical report, wherein the first biomedical report is generated fromdata or results based on the analysis of one or more nucleic acidsamples; (b) transmitting the first biomedical report to the user; (c)receiving, from the user, a second request for a second biomedicalreport differing from the first biomedical report, wherein (i) thesecond biomedical report is based on or derived from the firstbiomedical report, (ii) the second biomedical report is generated fromdata or results based on the analysis of one or more nucleic acidsamples, or (iii) a combination of (i)-(ii); and transmitting the secondbiomedical report to the user. The analysis of one or more nucleicsample of (a) and/or the analysis of one or more nucleic sample of (c)may comprise generating data or results based on or derived from theanalysis of two or more subsets of nucleic acid molecules. Transmittingthe second biomedical report may be based on the analysis of the firstbiomedical report.

Further disclosed herein is a method for generating one or morebiomedical reports, comprising (a) receiving, from a user, a firstrequest for a first biomedical report, wherein the first biomedicalreport is generated from data or results based on the analysis of one ormore nucleic acid samples; (b) analyzing, with the aid of a processor,one or more results from the first biomedical report; (c) transmitting asecond biomedical report to the user, wherein (i) the second biomedicalreport is based on or derived from the first biomedical report, (ii) thesecond biomedical report is generated from data or results based on theanalysis of one or more nucleic acid samples, or (iii) a combination of(i)-(ii). The analysis of one or more nucleic sample of (a) and/or theanalysis of one or more nucleic sample of (c) may comprise generatingdata or results based on or derived from the analysis of two or moresubsets of nucleic acid molecules.

The data or results of (a) and the data or results of (c) may be thesame. The data or results of (a) and the data or results of (c) may besimilar. The data or results of (a) and the data or results of (c) maybe different. The data or results of (a) and the data or results of (c)may be derived from or based on one or more assays. The data or resultsof (a) and the data or results of (c) may be derived from or based onthe same assay. The data or results of (a) and the data or results of(c) may be derived from or based on the similar assays. The data orresults of (a) and the data or results of (c) may be derived from orbased on two or more different assays. The data or results of (a) andthe data or results of (c) may be from one or more combined data orcombined results. The data or results of (a) and the data or results of(c) may be from the same combined data or combined results. The data orresults of (a) and the data or results of (c) may be from similarcombined data or combined results. The data or results of (a) and thedata or results of (c) may be from different combined data or combinedresults.

The methods and systems disclosed herein may further comprise one ormore memory locations to receive one or more requests from a user, storeone or more requests from a user, store the biomedical reports, or acombination thereof.

The methods and systems disclosed herein may further comprise one ormore additional processors for aggregating information from two or moredatabases. The methods and systems disclosed herein may further compriseone or more additional processors for generating one or more databaselibraries. The database libraries may comprise data or results from oneor more subsets of nucleic acid molecules. The database libraries maycomprise information at least a portion of two or more databases.

Additional aspects and advantages of the present disclosure will becomereadily apparent to those skilled in this art from the followingdetailed description, wherein only illustrative embodiments of thepresent disclosure are shown and described. As will be realized, thepresent disclosure is capable of other and different embodiments, andits several details are capable of modifications in various obviousrespects, all without departing from the disclosure. Accordingly, thedrawings and description are to be regarded as illustrative in nature,and not as restrictive.

INCORPORATION BY REFERENCE

All publications, patents, and patent applications mentioned in thisspecification are herein incorporated by reference to the same extent asif each individual publication, patent, or patent application wasspecifically and individually indicated to be incorporated by reference.

BRIEF DESCRIPTION OF THE DRAWINGS

The novel features of the invention(s) are set forth with particularityin the appended claims. A better understanding of the features andadvantages of the present invention(s) will be obtained by reference tothe following detailed description that sets forth illustrativeembodiments, in which the principles of the invention(s) are utilized,and the accompanying drawings (also “FIG.” and “FIGs.” herein), ofwhich:

FIG. 1. shows a system for implementing the methods of the disclosure.

FIGS. 2A-2D depict a schematic of four exemplary workflows of thepresent disclosure. The terms “Prep 1” and “Prep 2” may refer to subsetsof nucleic acid molecules; “Assay 1” and “Assay 2” may refer to assays.FIG. 2A depicts an assay and analysis workflow comprising purificationof DNA from a sample by two purification methods to produce two subsetsof purified DNA (Prep 1 and Prep 2). The two subsets of purified DNA arecombined and a single assay is conducted on the combined subsets.Lastly, a single analysis of the assay results is conducted and anoutput is generated. FIG. 2B depicts an assay and analysis workflowcomprising purification of DNA from a sample by two purification methodsto produce two subsets of purified DNA (Prep 1 and Prep 2). An assay isconducted on each subset. A single analysis of the results of the twoassays (Assay 1 and Assay 2) is conducted and an output is generated.FIG. 2C depicts an assay and analysis workflow comprising purificationof DNA from a sample by two purification methods to produce two subsetsof purified DNA (Prep 1 and Prep 2). An assay (Assay 1 and Assay 2) isconducted on each subset (Prep 1 and Prep 2). An analysis (Analysis 1and Analysis 2) is conducted on results from each assay. A single outputis generated based on the two separate analyses. FIG. 2D depicts anassay and analysis workflow comprising (1) separation of the nucleicacid sample into several subsets processed with several protocols. Theseprotocols may involve enrichment for different genomic or non-genomicregions and comprise one or more different amplification steps toprepare libraries of nucleic acid molecules for assay. Some of theselibraries may combined (2) for assay. Results of some assays may becombined (3) for subsequent analysis. Variant calls or other assessmentsof sequence or genetic state may be further combined (4) to produce acombined assessment at each locus addressed by the assay.

FIG. 3. depicts a schematic of a workflow of the present disclosure.

FIG. 4. depicts a schematic of a workflow of the present disclosure.

FIG. 5. shows effects of shear time on fragment size.

FIG. 6. shows effects of bead ratio on fragment size.

FIG. 7. shows effects of shear time on fragment size.

FIG. 8. depicts a schematic of a nucleic acid library constructionworkflow.

FIG. 9. depicts more detailed examples of the assay and analysisworkflows shown in FIG. 2A-2C.

FIG. 10. depicts a method for developing mutlithreaded assay addressingmultiple biomedical applications. Variants, genes, exons, UTRs,regulatory regions, splice sites, alternate sequences and other contentof interest are combined from several databases to produce an aggregateset of content which is applicable to multiple biomedical reports. Thiscontent is then categorized based on local or global genomic context,nucleotide content, sequencing performance and interpretation demandsand then subsequently grouped into subsets for specialized protocol andassay development.

FIG. 11. depicts an assay comprising multiple subsets of DNA enrichedfor different genomic regions, undergoing some independent processingsteps prior to being combined for a sequencing assay. Reads from the twoor more subsets are combined either a) in the sequencing device b)subsequently by means of one or more algorithms to produce a single bestresult for the regions addressed by the union of the two or more subsetsand resulting in a data pool that may be used for one or more biomedicalreports.

FIG. 12. depicts an assay comprising multiple subsets of DNA enrichedfor different genomic regions, undergoing some independent processingsteps prior to being independently sequenced and analyzed for variants.Variants from the two subsets are merged by means of one or morealgorithms to produce a single best result for the regions addressed bythe union of the two or more subsets and resulting in a data pool thatmay be used for one or more biomedical reports.

FIG. 13. depicts an assay comprising multiple subsets of DNA enrichedfor different genomic regions, undergoing some independent processingsteps prior to being independently sequenced and producing primary datawhich may include sequence reads. Primary data from the two or moreassays are combined and analyzed by one or more algorithms to produce asingle best result for all of the regions addressed by the union of thetwo or more subsets resulting in a data pool that may be used for one ormore biomedical reports.

FIG. 14. depicts a multi-threaded assay comprising two subsets of DNAproduced by size selection and one of these further divided into twosubsets of DNA enriched for different genomic regions based on GCcontent. The longer molecules undergo sequencing using a technologyappropriate for longer molecules. The two shorter molecule subsets arefurther prepared and amplified based on protocols appropriate to the Tmof the subsets then pooled for sequencing on a high throughput shortread sequencer, the HiSeq. In this example primary data from thesequencing is merged and analyzed by means of one or more algorithms toproduce a single best result for all of the regions addressed by thesubsets and resulting in a data pool that may be used for one or morebiomedical reports.

FIG. 15. depicts a multi-threaded assay comprising two subsets of DNAproduced by size selection and one of these further divided into twosubsets of DNA enriched for different genomic regions based on GCcontent. The longer molecules undergo sequencing using a technologyappropriate for longer molecules. The two shorter molecule subsets arefurther prepared and amplified based on protocols appropriate to the Tmof the subsets then pooled for sequencing on a high throughput shortread sequencer, the HiSeq. In this example primary data from the twosequencing technologies are analyzed separately for variants which arethen merged by means of one or more algorithms to produce a single bestresult for all of the regions addressed by the subsets and resulting ina data pool that may be used for one or more biomedical reports.

DETAILED DESCRIPTION

While various embodiments of the invention(s) of the present disclosurehave been shown and described herein, it will be obvious to thoseskilled in the art that such embodiments are provided by way of exampleonly. Numerous variations, changes, and substitutions may occur to thoseskilled in the art without departing from the invention(s). It should beunderstood that various alternatives to the embodiments of theinvention(s) described herein may be employed in practicing any one ofthe inventions(s) set forth herein.

This disclosure provides systems and methods for sample processing anddata analysis. In some cases, sample processing includes nucleic acidsample processing and subsequent nucleic acid sample sequencing. Some orall of a nucleic acid sample may be sequenced to provide sequenceinformation, which may be stored or otherwise maintained in anelectronic, magnetic or optical storage location. The sequenceinformation may be analyzed with the aid of a computer processor, andthe analyzed sequence information may be stored in an electronic storagelocation. The electronic storage location may include a pool orcollection of sequence information and analyzed sequence informationgenerated from the nucleic acid sample. The nucleic acid sample may beretrieved from a subject, such as, for example, a subject receivingtherapy.

In some cases, a user, such as a healthcare provider, may request afirst set of sequence information or analyzed sequence information fromthe pool. Concurrently or subsequently, the user may request a secondset of sequence information or analyzed sequence information from thepool. The first set may be different from the second set.

The term “nucleic acid” as used herein generally refers to a polymericform of nucleotides of any length, either ribonucleotides,deoxyribonucleotides or peptide nucleic acids (PNAs), that comprisepurine and pyrimidine bases, or other natural, chemically orbiochemically modified, non-natural, or derivatized nucleotide bases.The backbone of the polynucleotide can comprise sugars and phosphategroups, as may typically be found in RNA or DNA, or modified orsubstituted sugar or phosphate groups. A polynucleotide may comprisemodified nucleotides, such as methylated nucleotides and nucleotideanalogs. The sequence of nucleotides may be interrupted bynon-nucleotide components. Thus the terms nucleoside, nucleotide,deoxynucleoside and deoxynucleotide generally include analogs such asthose described herein. These analogs are those molecules having somestructural features in common with a naturally occurring nucleoside ornucleotide such that when incorporated into a nucleic acid oroligonucleoside sequence, they allow hybridization with a naturallyoccurring nucleic acid sequence in solution. Typically, these analogsare derived from naturally occurring nucleosides and nucleotides byreplacing and/or modifying the base, the ribose or the phosphodiestermoiety. The changes can be tailor made to stabilize or destabilizehybrid formation or enhance the specificity of hybridization with acomplementary nucleic acid sequence as desired. The nucleic acidmolecule may be a DNA molecule. The nucleic acid molecule may be an RNAmolecule.

As used herein, the terms “variant or derivative of a nucleic acidmolecule” or “derivative or variant of a nucleic acid molecule”generally refer to a nucleic acid molecule comprising a polymorphism.The terms “variant or derivative of a nucleic acid molecule” or“derivative or variant of a nucleic acid molecule” may also refer tonucleic acid product that is produced from one or more assays conductedon the nucleic acid molecule. For example, a fragmented nucleic acidmolecule, hybridized nucleic acid molecule (e.g., capture probehybridized nucleic acid molecule, bead bound nucleic acid molecule),amplified nucleic acid molecule, isolated nucleic acid molecule, elutednucleic acid molecule, and enriched nucleic acid molecule are variantsor derivatives of the nucleic acid molecule.

The terms “detectable label” or “label” as used herein generally refersto any chemical moiety attached to a nucleotide, nucleotide polymer, ornucleic acid binding factor, wherein the attachment may be covalent ornon-covalent. Preferably, the label is detectable and renders thenucleotide or nucleotide polymer detectable to the practitioner of theinvention. The terms “detectable label” or “label” may be usedinterchangeably. Detectable labels that may be used in combination withthe methods disclosed herein include, for example, a fluorescent label,a chemiluminescent label, a quencher, a radioactive label, biotin,quantum dot, gold, or a combination thereof. Detectable labels includeluminescent molecules, fluorochromes, fluorescent quenching agents,colored molecules, radioisotopes or scintillants. Detectable labels alsoinclude any useful linker molecule (such as biotin, avidin,streptavidin, HRP, protein A, protein G, antibodies or fragmentsthereof, Grb2, polyhistidine, Ni²+, FLAG tags, myc tags), heavy metals,enzymes (examples include alkaline phosphatase, peroxidase andluciferase), electron donors/acceptors, acridinium esters, dyes andcalorimetric substrates. It is also envisioned that a change in mass maybe considered a detectable label, as is the case of surface plasmonresonance detection. The skilled artisan would readily recognize usefuldetectable labels that are not mentioned above, which may be employed inthe operation of the present invention.

The terms “bound”, “hybridized”, “conjugated”, “attached”, “linked” canbe used interchangeably and generally refer to the association of aobject to another object. The association of the two objects to eachother may be from a covalent or non-covalent interaction. For example, acapture probe hybridized nucleic acid molecule refers a capture probeassociated with a nucleic acid molecule. The capture probe and thenucleic acid molecule are in contact with each other. In anotherexample, a bead bound nucleic acid molecule refers to a bead associatedwith a nucleic acid molecule.

Disclosed herein are methods for analyzing a nucleic acid sample. Themethods of the disclosure may comprise (a) producing two or more subsetsof nucleic acid molecules from a nucleic acid sample comprising one ormore nucleic acid molecules; (b) enriching the two or more subsets ofnucleic acid molecules for two or more different subsets of a genomicregion; (c) conducting an assay on each of the two subsets of nucleicacid molecules, wherein (i) a first assay, comprising a first sequencingreaction, is conducted on the first subset of the two or more subsets ofnucleic acid molecules to produce a first result, and (ii) a secondassay is conducted on the second subset of the two or more subsets toproduce a second result; and (d) combining, with the aid of a computerprocessor, the first result and the second result, thereby analyzing thenucleic acid sample.

In an aspect of the present disclosure, methods for nucleic acidprocessing and/or analysis are provided. The methods disclosed hereinmay comprise (a) producing two or more subsets of nucleic acid moleculesfrom a nucleic acid sample; (b) combining at least two of the two ormore subsets of nucleic acid molecules to produce a combined pool ofnucleic acid molecules; and (c) conducting one or more assays on thecombined pool of nucleic acid molecules, wherein at least one of the oneor more assays comprises a sequencing reaction.

Provided herein are methods comprising (a) producing two or more subsetsof nucleic acid molecules from a nucleic acid sample; (b) enriching thetwo or more subsets of nucleic acid molecules for two or more differentsubsets of a genomic region; (c) conducting a first assay on a firstsubset of nucleic acid molecules among the two or more subsets ofnucleic acid molecules to produce a first result, wherein the firstassay comprises a first sequencing reaction; (d) conducting a secondassay on at least a second subset of nucleic acid molecules among thetwo or more subsets of nucleic acid molecules to produce a secondresult; and (e) combining, with the aid of a computer processor, thefirst result with the second result, thereby analyzing the nucleic acidsample.

Also disclosed herein are methods comprising (a) preparing at least afirst subset of nucleic acid molecules and a second subset of nucleicacid molecules from a nucleic acid sample; (b) enriching the first andsecond subsets of nucleic acid molecules for at least two subsets of agenomic region; (c) conducting a first assay on the first subset ofnucleic acid molecules and a second assay on the second subset ofnucleic acid molecules, wherein the first assay comprises a nucleic acidsequencing reaction that produces a first result, comprising nucleicacid sequence information for the first subset, and wherein the secondassay produces a second result; (d) analyzing, with the aid of acomputer processor, the first result to provide a first analyzed resultand analyzing the second result to provide a second analyzed result; and(e) combining, with the aid of a computer processor, the first andsecond analyzed results, thereby analyzing the nucleic acid sample.

Disclosed herein are methods, comprising (a) conducting a first assay ona nucleic acid sample, wherein the first assay comprises one or moreantioxidants; and (b) conducting a sequencing reaction on the nucleicacid sample, thereby analyzing the nucleic acid sample.

Further provided herein are methods comprising (a) producing, with theaid of a computer processor, one or more capture probes, wherein the oneor more capture probes hybridize to one or more polymorphisms; (b)contacting a nucleic acid sample with the one or more capture probes toproduce one or more capture probe hybridized nucleic acid molecules; and(c) conducting a sequencing reaction on the one or more capture probehybridized nucleic acid molecules, thereby analyzing the nucleic acidsample.

Further disclosed herein are methods for analyzing a nucleic acidmolecule. The methods may comprise (a) contacting a nucleic acid samplewith one or more capture probes, wherein at least one of the one or morecapture probes hybridize to a structural variant within, near orspanning an entire gene or at least a portion of a gene of to produceone or more capture probe hybridized nucleic acid molecules; and (b)conducting a sequencing reaction on the one or more capture probehybridized nucleic acid molecules, thereby analyzing the gene. The oneor more capture probes may additionally hybridize to one or more genomicregions disclosed herein.

Provided herein are methods comprising (a) conducting a first assay on anucleic acid sample, wherein the first assay comprises fragmenting oneor more nucleic acid molecules in the nucleic acid sample to produce oneor more first fragmented nucleic acid molecules; (b) conducting a secondassay on the nucleic acid sample, wherein the second assay comprisescontacting at least a portion of the one or more first fragmentednucleic acid molecules with a first set of beads to produce a one ormore first bead bound nucleic acid molecules; and (c) conducting a thirdassay on the nucleic acid sample, wherein the third assay comprisescontacting at least a portion of the first fragmented nucleic acidmolecules with a second set of beads to produce one or more second beadbound nucleic acid molecules, thereby preparing the nucleic acid sample.

Disclosed herein are methods comprising (a) producing two or moresubsets of nucleic acid molecules from a sample, wherein (i) the two ormore subsets of nucleic acid molecules comprise a first subset ofnucleic acid molecules and a second subset of nucleic acid molecules,(ii) the first subset of nucleic acid molecules comprises nucleic acidmolecules of a first mean size, (iii) the second subset of nucleic acidmolecules comprises nucleic acid molecules of a second mean size, and(iv) the first mean size of the first subset of nucleic acid moleculesis greater than the second mean size of the second subset of nucleicacid molecules by about 200 or more residues; and (b) producing two ormore nucleic acid libraries, wherein (i) the two or more librariescomprise a first nucleic acid library and second nucleic acid library,(ii) the first nucleic acid library comprises the one or more first beadbound nucleic acid molecules, (iii) the second nucleic acid librarycomprises the one or more second bead bound nucleic acid molecules, and(iv) the content of the first nucleic acid library is at least partiallycomplementary to the content of the second nucleic acid library.

Disclosed herein are methods comprising (a) producing two or moresubsets of nucleic acid molecules from a sample comprising one or morenucleic acid molecules, wherein the two or more subsets of nucleic acidmolecules comprise a first subset of nucleic acid molecules and a secondsubset of nucleic acid molecules; (b) conducting two or more assays onthe two or more subsets of nucleic acid molecules, wherein (i) the twoor more assays comprise a first assay and a second assay, (ii) the firstassay comprises conducting a first amplification reaction on the firstsubset of nucleic acid molecules to produce one or more first ampliconswith a first mean GC content, (iii) the second assay comprisesconducting a second amplification reaction on the second subset ofnucleic acid molecules to produce one or more second amplicons with asecond mean GC content, and (iv) the first mean GC content of the firstsubset of nucleic acid molecules differs from the second mean GC contentof the second subset of nucleic acid molecules; and producing two ormore nucleic acid libraries, wherein (i) the two or more librariescomprise a first nucleic acid library and second nucleic acid library,(ii) the first nucleic acid library comprises the one or more firstamplicons, (iii) the second nucleic acid library comprises the one ormore second amplicons, and (iv) the content of the first nucleic acidlibrary is at least partially complementary to the content of the secondnucleic acid library.

Provided herein are methods comprising (a) producing two or more subsetsof nucleic acid molecules from a sample comprising one or more nucleicacid molecules, wherein (i) the two or more subsets of nucleic acidmolecules comprise a first subset of nucleic acid molecules and a secondsubset of nucleic acid molecules, and (ii) the two or more subsets ofnucleic acid molecules differ by one or more genomic region features;and (b) producing two or more nucleic acid libraries, wherein (i) thetwo or more libraries comprise a first nucleic acid library and secondnucleic acid library, (ii) the first nucleic acid library comprises theone or more first bead bound nucleic acid molecules, (iii) the secondnucleic acid library comprises the one or more second bead bound nucleicacid molecules, and (iv) the content of the first nucleic acid libraryis at least partially complementary to the content of the second nucleicacid library.

Further provided herein are methods for sequencing a nucleic acidmolecule. The methods may comprise (a) contacting a nucleic acid samplewith two or more capture probe sets to produce a plurality of captureprobe hybridized nucleic acid molecules, wherein the plurality ofcapture probe hybridized nucleic acid molecules comprise to two or morenucleic acid molecules regions selected from the group comprising (i)high GC content; (ii) low GC content; (iii) low complexity; (iv) lowmappability; (v) known single nucleotide variations (SNVs); (vi) knowninDels; (vii) known alternative sequences comprising one or more smallinsertions, small deletions, structural variant junctions, variablelength tandem repeats, or flanking sequences; (viii) entire genome; (ix)entire exome; (x) set of genes with known Mendelian traits; (xi) set ofgenes; (xii) a set of regulatory elements; (xiii) set of genes withknown disease traits; (xiv) set of genes with known drug traits; and(xv) set of genes with known biomedically interpretable variants; and(b) conducting a sequencing reaction on the plurality of capture probehybridized nucleic acid molecules.

In some aspects of the disclosure, The methods comprise (a) contacting anucleic acid sample with one or more capture probes, wherein at leastone of the one or more capture probes hybridize to two or more differentgenomic regions within, near or spanning the gene of interest to produceone or more capture probe hybridized nucleic acid molecules; and (b)conducting a sequencing reaction on the one or more capture probehybridized nucleic acid molecules, thereby analyzing the gene ofinterest.

Further disclosed herein, in some aspects of the disclosure, are methodsfor generating a biomedical report. The methods may comprise (a)receiving, from a user, a first request for a first specified biomedicalreport, wherein (i) the first specified heath report is generated fromdata or results based on the analysis of two or more subsets of nucleicacid molecules from a nucleic acid sample, and (ii) the two or moresubsets of nucleic acid molecules differ by one or more features; (b)transmitting the first specified biomedical report to the user; (c)receiving, from the user, a second request for a second specifiedbiomedical report, wherein (i) the second specified heath report isgenerated from the data or results based on the analysis of two or moresubsets of nucleic acid molecules from the nucleic acid sample, (ii) thetwo or more subsets of nucleic acid molecules differ by one or morefeatures, and (iii) the first specified biomedical report and the secondspecified biomedical report differ by one or more biomedical features;and (c0 transmitting the second specified biomedical report to the user.

Further disclosed herein, in some aspects of the disclosure, arecomplementary nucleic acid libraries, wherein the libraries arecomplementary in one or more aspects. The one or more aspects may beselected from the group comprising GC content, fragment length, andgenomic region. Also disclosed herein are methods and systems fordeveloping these libraries and kits comprising these libraries.

Provided herein, in some aspects of the disclosure, are kits comprisingone or more capture probe sets. The kits may comprise a first captureprobe set and a second capture probe set, wherein (i) the first andsecond capture probe sets hybridize to one or more genomic regions and(ii) one or more of the genomic regions hybridized by the first captureprobe set are different from one or more of the genomic regionshybridized by the second capture probe set.

Before the present methods are described in further detail, it is to beunderstood that this invention is not limited to particular method orcomposition described, as such may, of course, vary. It is also to beunderstood that the terminology used herein is for the purpose ofdescribing particular embodiments only, and is not intended to belimiting, since the scope of the present invention will be limited onlyby the appended claims. Examples are put forth so as to provide those ofordinary skill in the art with a complete disclosure and description ofhow to make and use the present invention, and are not intended to limitthe scope of what the inventors regard as their invention nor are theyintended to represent that the experiments below are all or the onlyexperiments performed. Efforts have been made to ensure accuracy withrespect to numbers used (e.g. amounts, temperature, etc.) but someexperimental errors and deviations should be accounted for. Unlessindicated otherwise, parts are parts by weight, molecular weight isweight average molecular weight, temperature is in degrees Centigrade,and pressure is at or near atmospheric.

Where a range of values is provided, it is understood that eachintervening value, to the tenth of the unit of the lower limit unlessthe context clearly dictates otherwise, between the upper and lowerlimits of that range is also specifically disclosed. Each smaller rangebetween any stated value or intervening value in a stated range and anyother stated or intervening value in that stated range is encompassedwithin the invention. The upper and lower limits of these smaller rangesmay independently be included or excluded in the range, and each rangewhere either, neither or both limits are included in the smaller rangesis also encompassed within the invention, subject to any specificallyexcluded limit in the stated range. Where the stated range includes oneor both of the limits, ranges excluding either or both of those includedlimits are also included in the invention.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this invention belongs. Although any methods andmaterials similar or equivalent to those described herein can be used inthe practice or testing of the present invention, some potential andpreferred methods and materials are now described. All publicationsmentioned herein are incorporated herein by reference to disclose anddescribe the methods and/or materials in connection with which thepublications are cited. It is understood that the present disclosuresupercedes any disclosure of an incorporated publication to the extentthere is a contradiction.

As will be apparent to those of skill in the art upon reading thisdisclosure, each of the individual embodiments described and illustratedherein has discrete components and features which may be readilyseparated from or combined with the features of any of the other severalembodiments without departing from the scope or spirit of the presentinvention. Any recited method can be carried out in the order of eventsrecited or in any other order which is logically possible.

It must be noted that as used herein and in the appended claims, thesingular forms “a”, “an”, and “the” include plural referents unless thecontext clearly dictates otherwise. Thus, for example, reference to “acell” includes a plurality of such cells and reference to “the peptide”includes reference to one or more peptides and equivalents thereof, e.g.polypeptides, known to those skilled in the art, and so forth.

The publications discussed herein are provided solely for theirdisclosure prior to the filing date of the present application. Nothingherein is to be construed as an admission that the present invention isnot entitled to antedate such publication by virtue of prior invention.Further, the dates of publication provided may be different from theactual publication dates which may need to be independently confirmed.

The disclosures herein merely illustrate the principles of theinvention. It will be appreciated that those skilled in the art will beable to devise various arrangements which, although not explicitlydescribed or shown herein, embody the principles of the invention andare included within its spirit and scope. Furthermore, all examples andconditional language recited herein are principally intended to aid thereader in understanding the principles of the invention and the conceptscontributed by the inventors to furthering the art, and are to beconstrued as being without limitation to such specifically recitedexamples and conditions. Moreover, all statements herein recitingprinciples, aspects, and embodiments of the invention as well asspecific examples thereof, are intended to encompass both structural andfunctional equivalents thereof. Additionally, it is intended that suchequivalents include both currently known equivalents and equivalentsdeveloped in the future, e.g., any elements developed that perform thesame function, regardless of structure. The scope of the presentinvention, therefore, is not intended to be limited to the exemplaryembodiments shown and described herein. Rather, the scope and spirit ofthe present invention is embodied by the appended claims.

Subsets of Nucleic Acid Molecules

The methods disclosed herein may comprise one or more subsets of nucleicacid molecules. The subsets of nucleic acid molecules may be derivedfrom a nucleic acid sample. The subsets of nucleic acid molecules may bederived from the same nucleic acid sample. Alternatively, oradditionally, the subsets of nucleic acid molecules are derived from twoor more different nucleic acid samples. Two or more subsets of nucleicacid molecules may be differentiated by their nucleic acid content. Theone or more subsets of nucleic acid molecules may comprise one or morenucleic acid molecules or a variant or derivative thereof. For example,the two or more subsets of nucleic acid molecules may comprise nucleicacids comprising different GC content, nucleic acid size, genomicregions, genomic region features, eluted nucleic acid molecules,hybridized nucleic acid molecules, non-hybridized nucleic acidmolecules, amplified nucleic acid molecules, non-amplified nucleic acidmolecules, supernatant-derived nucleic acid molecules, eluant-derivednucleic acid molecules, labeled nucleic acid molecules, non-labelednucleic acid molecules, capture probe hybridized nucleic acid molecules,capture probe free nucleic acid molecules, bead bound nucleic acidmolecules, bead free nucleic acid molecules, or a combination thereof.The two or more subsets of nucleic acid molecules may be differentiatedby GC content, nucleic acid size, genomic regions, capture probes,beads, labels, or a combination thereof.

The methods disclosed herein may comprise combining two or more subsetsof nucleic acid molecules to produce a combined subset of nucleic acidmolecules. The combined subsets of nucleic acid molecules may be derivedfrom a nucleic acid sample. The combined subsets of nucleic acidmolecules may be derived from the same nucleic acid sample.Alternatively, or additionally, the combined subsets of nucleic acidmolecules are derived from two or more different nucleic acid samples.Two or more combined subsets of nucleic acid molecules may bedifferentiated by their nucleic acid content. The one or more combinedsubsets of nucleic acid molecules may comprise one or more nucleic acidmolecules or a variant or derivative thereof. For example, the two ormore combined subsets of nucleic acid molecules may comprise nucleicacids comprising different GC content, nucleic acid size, genomicregions, genomic region features, eluted nucleic acid molecules,hybridized nucleic acid molecules, non-hybridized nucleic acidmolecules, amplified nucleic acid molecules, non-amplified nucleic acidmolecules, supernatant-derived nucleic acid molecules, eluant-derivednucleic acid molecules, labeled nucleic acid molecules, non-labelednucleic acid molecules, capture probe hybridized nucleic acid molecules,capture probe free nucleic acid molecules, bead bound nucleic acidmolecules, bead free nucleic acid molecules, or a combination thereof.The two or more combined subsets of nucleic acid molecules may bedifferentiated by GC content, nucleic acid size, genomic regions,capture probes, beads, labels, or a combination thereof.

Subsets of nucleic acid molecules may comprise one or more genomicregions as disclosed herein. Subsets of nucleic acid molecules maycomprise 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 6 ormore, 7 or more, 8 or more, 9 or more, 10 or more, 11 or more, 12 ormore, 13 or more, 14 or more, 15 or more, 20 or more, 25 or more, 30 ormore, 35 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 ormore, 90 or more, or 100 or more genomic regions. The one or moregenomic regions may be identical, similar, different, or a combinationthereof.

Subsets of nucleic acid molecules may comprise one or more genomicregion features as disclosed herein. Subsets of nucleic acid moleculesmay comprise 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 6 ormore, 7 or more, 8 or more, 9 or more, 10 or more, 11 or more, 12 ormore, 13 or more, 14 or more, 15 or more, 20 or more, 25 or more, 30 ormore, 35 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 ormore, 90 or more, or 100 or more genomic region features. The one ormore genomic region features may be identical, similar, different, or acombination thereof.

Subsets of nucleic acid molecules may comprise nucleic acid molecules ofdifferent sizes. The length of a nucleic acid molecule in a subset ofnucleic acid molecules may be referred to as the size of the nucleicacid molecule. The average length of the nucleic acid molecules in asubset of nucleic acid molecules may be referred to as the mean size ofnucleic acid molecules. As used herein, the terms “size of a nucleicacid molecule”, “mean size of nucleic acid molecules”, “molecular size”and “mean molecular size” may be used interchangeably. The size of anucleic acid molecule may be used to differentiate two or more subsetsof nucleic acid molecules. The difference in the mean size of nucleicacid molecules in a subset of nucleic acid molecules and the mean sizeof nucleic acid molecules in another subset of nucleic acid moleculesmay be used to differentiate the two subsets of nucleic acid molecules.The mean size of nucleic acid molecules in one subset of nucleic acidmolecules may be greater than the mean size of nucleic acid molecules inat least one other subset of nucleic acid molecules. The mean size ofnucleic acid molecules in one subset of nucleic acid molecules may beless than the mean size of nucleic acid molecules in at least one othersubset of nucleic acid molecules. The difference in mean molecular sizebetween two or more subsets of nucleic acid molecules may be at leastabout 50; 75; 100; 125; 150; 175; 200; 225; 250; 275; 300; 350; 400;450; 500; 550; 600; 650; 700; 750; 800; 850; 900; 950; 1,000; 1100;1200; 1300; 1400; 1500; 1600; 1700; 1800; 1900; 2,000; 3,000; 4,000;5,000; 6,000; 7,000; 8,000; 9,000; 10,000; 15,000; 20,000; 30,000;40,000; 50,000; 60,000; 70,000; 80,000; 90,000; 100,000 or more bases orbase pairs. In some aspects of the disclosure, the difference in meanmolecular size between two or more subsets of nucleic acid molecules isat least about 200 bases or bases pairs. Alternatively, the differencein mean molecular size between two or more subsets of nucleic acidmolecules is at least about 300 bases or bases pairs.

Subsets of nucleic acid molecules may comprise nucleic acid molecules ofdifferent sequencing sizes. The length of a nucleic acid molecule in asubset of nucleic acid molecules to be sequenced may be referred to asthe sequencing size of the nucleic acid molecule. The average length ofthe nucleic acid molecules in a subset of nucleic acid molecules may bereferred to as the mean sequencing size of nucleic acid molecules. Asused herein, the terms “sequencing size of a nucleic acid molecule”,“mean sequencing size of nucleic acid molecules”, “molecular sequencingsize” and “mean molecular sequencing size” may be used interchangeably.The mean molecular sequencing size of one or more subsets of nucleicacid molecules may be at least about 50; 75; 100; 125; 150; 175; 200;225; 250; 275; 300; 350; 400; 450; 500; 550; 600; 650; 700; 750; 800;850; 900; 950; 1,000; 1100; 1200; 1300; 1400; 1500; 1600; 1700; 1800;1900; 2,000; 3,000; 4,000; 5,000; 6,000; 7,000; 8,000; 9,000; 10,000;15,000; 20,000; 30,000; 40,000; 50,000; 60,000; 70,000; 80,000; 90,000;100,000 or more bases or base pairs. The sequencing size of a nucleicacid molecule may be used to differentiate two or more subsets ofnucleic acid molecules. The difference in the mean sequencing size ofnucleic acid molecules in a subset of nucleic acid molecules and themean sequencing size of nucleic acid molecules in another subset ofnucleic acid molecules may be used to differentiate the two subsets ofnucleic acid molecules. The mean sequencing size of nucleic acidmolecules in one subset of nucleic acid molecules may be greater thanthe mean sequencing size of nucleic acid molecules in at least one othersubset of nucleic acid molecules. The mean sequencing size of nucleicacid molecules in one subset of nucleic acid molecules may be less thanthe mean sequencing size of nucleic acid molecules in at least one othersubset of nucleic acid molecules. The difference in mean molecularsequencing size between two or more subsets of nucleic acid moleculesmay be at least about 50; 75; 100; 125; 150; 175; 200; 225; 250; 275;300; 350; 400; 450; 500; 550; 600; 650; 700; 750; 800; 850; 900; 950;1,000; 1100; 1200; 1300; 1400; 1500; 1600; 1700; 1800; 1900; 2,000;3,000; 4,000; 5,000; 6,000; 7,000; 8,000; 9,000; 10,000; 15,000; 20,000;30,000; 40,000; 50,000; 60,000; 70,000; 80,000; 90,000; 100,000 or morebases or base pairs. In some aspects of the disclosure, the differencein mean molecular sequencing size between two or more subsets of nucleicacid molecules is at least about 200 bases or bases pairs.Alternatively, the difference in mean molecular sequencing size betweentwo or more subsets of nucleic acid molecules is at least about 300bases or bases pairs.

Two or more subsets of nucleic acid molecules may be at least partiallycomplementary. For example, a first subset of nucleic acid molecules maycomprise nucleic acid molecules comprising at least a first portion ofthe genome and a second subset of nucleic acid molecules may comprisenucleic acid molecules comprising at least a second portion of thegenome, wherein the first and second portion of the genome differ by oneor more nucleic acid molecules. Thus, the first subset and the secondsubset are at least partially complementary. The complementarity of twoor more subsets of nucleic acid molecules may be at least about 10%,15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%,85%, 90%, 95%, 97%, or more. As used herein, the term “complementarityof two or more subsets of nucleic acid molecules” generally refers togenomic content of the two or more subsets and the extent to which thetwo or more subsets encompass the content of one or more genomicregions. For example, a first subset of nucleic acid molecules comprises50% of total high GC exomes and a second subset of nucleic acidmolecules comprises 50% of the total low GC exomes, then thecomplementarity of the two subsets of nucleic acid molecules inreference to an entire exome is 50%. In another example, a first subsetof nucleic acid molecules comprises 100% of the total bead bound nucleicacid molecules and the second subset of nucleic acid molecules comprises100% of the total bead free nucleic acid molecules, the complementarityof the two subsets in reference to the total nucleic acid molecules is100%.

Subsets of nucleic acid molecules may comprise bead bound nucleic acidmolecules. Two or more subsets of nucleic acid molecules may bedifferentiated into bead bound nucleic acid molecules and bead freenucleic acid molecules. For example, a first subset of nucleic acidmolecules may comprise one or more bead bound nucleic acid molecules anda second subset of nucleic acid molecules may comprise bead free nucleicacid molecules. Bead free nucleic acid molecules may refer to nucleicacid molecules that are not bound to one or more beads. Bead freenucleic acid molecules may refer to nucleic acid molecules that havebeen eluted from one or more beads. For example, the nucleic acidmolecule from a bead bound nucleic acid molecule may be eluted toproduce a bead free nucleic acid molecule.

Subsets of nucleic acid molecules may comprise capture probe hybridizednucleic acid molecules. Two or more subsets of nucleic acid moleculesmay be differentiated into capture probe hybridized nucleic acidmolecules and capture probe free nucleic acid molecules. For example, afirst subset of nucleic acid molecules may comprise one or more captureprobe hybridized nucleic acid molecules and a second subset of nucleicacid molecules may comprise capture probe free nucleic acid molecules.Capture probe free nucleic acid molecules may refer to nucleic acidmolecules that are not hybridized to one or more capture probes. Captureprobe free nucleic acid molecules may refer to nucleic acid moleculesthat are dehybridized from one or more capture probes. For example, thecapture probe from a capture probe hybridized nucleic acid molecule maybe removed to produce a capture probe free nucleic acid molecule.

Capture probes may hybridize to one or more nucleic acid molecules in asample or in a subset of nucleic acid molecules. Capture probes mayhybridize to one or more genomic regions. Capture probes may hybridizeto one or more genomic regions within, around, near, or spanning one ormore genes, exons, introns, UTRs, or a combination thereof. Captureprobes may hybridize to one or more genomic regions spanning one or moregenes, exons, introns, UTRs, or a combination thereof. Capture probesmay hybridize to one or more known inDels. Capture probes may hybridizeto one or more known structural variants.

Subsets of nucleic acid molecules may comprise labeled nucleic acidmolecules. Two or more subsets of nucleic acid molecules may bedifferentiated into labeled nucleic acid molecules and non-labelednucleic acid molecules. For example, a first subset of nucleic acidmolecules may comprise one or more labeled nucleic acid molecules and asecond subset of nucleic acid molecules may comprise non-labeled nucleicacid molecules. Non-labeled nucleic acid molecules may refer to nucleicacid molecules that are not attached to one or more labels. Non-labelednucleic acid molecules may refer to nucleic acid molecules that havebeen detached from one or more labels. For example, the label from alabeled nucleic acid molecule may be removed to produce a non-labelednucleic acid molecule.

The methods disclosed herein may comprise one or more labels. The one ormore labels may be attached to one or more capture probes, nucleic acidmolecules, beads, primers, or a combination thereof. Examples of labelsinclude, but are not limited to, detectable labels, such asradioisotopes, fluorophores, chemiluminophores, chromophore, lumiphore,enzymes, colloidal particles, and fluorescent microparticles, quantumdots, as well as antigens, antibodies, haptens, avidin/streptavidin,biotin, haptens, enzymes cofactors/substrates, one or more members of aquenching system, a chromogens, haptens, a magnetic particles, materialsexhibiting nonlinear optics, semiconductor nanocrystals, metalnanoparticles, enzymes, aptamers, and one or more members of a bindingpair.

The one or more subsets of nucleic acid molecules may be subjected toone or more assays. The one or more subsets of nucleic acid moleculesmay be subjected to one or more assays based on their biochemicalfeatures. The one or more subsets of nucleic acid molecules may besubjected to one or more assays based on their genomic region features.The one or more subsets of nucleic acid molecules may be subjected to 1,2, 3, 4, 5, 6, 7, 8, 9, 10 or more assays. The one or more subsets ofnucleic acid molecules may be subjected to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10or more assays based on their biochemical features. The one or moresubsets of nucleic acid molecules may be subjected to 1, 2, 3, 4, 5, 6,7, 8, 9, 10 or more assays based on their genomic region features. Theone or more subsets of nucleic acid molecules may be subjected to 1, 2,3, 4, 5, 6, 7, 8, 9, 10 or more identical assays. The one or moresubsets of nucleic acid molecules may be subjected to 1, 2, 3, 4, 5, 6,7, 8, 9, 10 or more identical assays based on their biochemicalfeatures. The one or more subsets of nucleic acid molecules may besubjected to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or more identical assaysbased on their genomic region features. The one or more subsets ofnucleic acid molecules may be subjected to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10or more similar assays. The one or more subsets of nucleic acidmolecules may be subjected to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or moresimilar assays based on their biochemical features. The one or moresubsets of nucleic acid molecules may be subjected to 1, 2, 3, 4, 5, 6,7, 8, 9, 10 or more similar assays based on their genomic regionfeatures. The one or more subsets of nucleic acid molecules may besubjected to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or more different assays. Theone or more subsets of nucleic acid molecules may be subjected to 1, 2,3, 4, 5, 6, 7, 8, 9, 10 or more different assays based on theirbiochemical features. The one or more subsets of nucleic acid moleculesmay be subjected to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or more differentassays based on their genomic region features. The two or more subsetsof nucleic acid molecules may be subjected to one or more identicalprocessing steps based on their biochemical features. The two or moresubsets of nucleic acid molecules may be subjected to one or moreidentical processing steps based on their genomic region features. Thetwo or more subsets of nucleic acid molecules may be subjected to one ormore similar processing steps based on their biochemical features. Thetwo or more subsets of nucleic acid molecules may be subjected to one ormore similar processing steps based on their genomic region features.The two or more subsets of nucleic acid molecules may be subjected toone or more different processing steps based on their biochemicalfeatures. The two or more subsets of nucleic acid molecules may besubjected to one or more different processing steps based on theirgenomic region features.

The methods disclosed herein may comprise producing two or more subsetsof nucleic acid molecules. The two or more subsets of nucleic acidmolecules may be separated fluidically, separated into two or morecontainers, separated into two or more locations, or a combinationthereof. For example, a first subset of nucleic acid molecules and asecond subset of nucleic acid molecules are fluidically separated. Inanother example, a first subset of nucleic acid molecules is in a firstcontainer and second subset of nucleic acid molecules is in a secondcontainer. In yet another example, a first subset of nucleic acidmolecules and a second subset of nucleic acid molecules are assigned totwo or more locations on a first container, and a third subset ofnucleic acid molecules is in a second container.

Genomic Regions

The methods disclosed herein may comprise nucleic acid samples orsubsets of nucleic acid molecules comprising one or more genomicregions. The methods disclosed herein may comprise nucleic acid samplesor subsets of nucleic acid molecules comprising one or more sets ofgenomic regions. The one or more genomic regions may comprise one ormore genomic region features. The genomic region features may comprisean entire genome or a portion thereof. The genomic region features maycomprise an entire exome or a portion thereof. The genomic regionfeatures may comprise one or more sets of genes. The genomic regionfeatures may comprise one or more genes. The genomic region features maycomprise one or more sets of regulatory elements. The genomic regionfeatures may comprise one or more regulatory elements. The genomicregion features may comprise a set of polymorphisms. The genomic regionfeatures may comprise one or more polymorphisms. The genomic regionfeature may relate to the GC content, complexity, and/or mappability ofone or more nucleic acid molecules. The genomic region features maycomprise one or more simple tandem repeats (STRs), unstable expandingrepeats, segmental duplications, single and paired read degenerativemapping scores, GRCh37 patches, or a combination thereof. The genomicregion features may comprise one or more low mean coveage regions fromwhole genome sequencing (WGS), zero mean coverage regions from WGS,validated compressions, or a combination thereof. The genomic regionfeatures may comprise one or more alternate or non-reference sequences.The genomic region features may comprise one or more gene phasing andreassembly genes. In some aspects of the disclosure, the one or moregenomic region features are not mutually exclusive. For example, agenomic region feature comprising an entire genome or a portion thereofcan overlap with an additional genomic region feature such as an entireexome or a portion thereof, one or more genes, one or more regulatoryelements, etc. Alternatively, the one or more genomic region futures aremutually exclusive. For example, a genomic region comprising thenoncoding portion of an entire genome would not overlap with a genomicregion feature such as an exome or portion thereof or the coding portionof a gene. Alternatively, or additionally, the one or more genomicregion features are partially exclusive or partially inclusive. Forexample, a genomic region comprising an entire exome or a portionthereof can partially overlap with a genomic region comprising an exonportion of a gene. However, the genomic region comprising the entireexome or portion thereof would not overlap with the genomic regioncomprising the intron portion of the gene. Thus, a genomic regionfeature comprising a gene or portion thereof may partially excludeand/or partially include a genomic region feature comprising an entireexome or portion thereof.

The methods disclosed herein may comprise nucleic acid samples orsubsets of nucleic acid molecules comprising one or more genomicregions, wherein at least one of the one or more genomic regionscomprises a genomic region feature comprising an entire genome orportion thereof. The entire genome or portion thereof may comprise oneor more coding portions of the genome, one or more noncoding portions ofthe genome, or a combination thereof. The coding portion of the genomemay comprise one or more coding portions of a gene encoding for one ormore proteins. The one or more coding portions of the genome maycomprise an entire exome or a portion thereof. Alternatively, oradditionally, the one or more coding portions of the genome may compriseone or more exons. The one or more noncoding portions of the genome maycomprise one or more noncoding molecules or a portion thereof. Thenoncoding molecules may comprise one or more noncoding RNA, one or moreregulatory elements, one or more introns, one or more pseudogenes, oneor more repeat sequences, one or more transposons, one or more viralelements, one or more telomeres, a portion thereof, or a combinationthereof. The noncoding RNAs may be functional RNA molecules that are nottranslated into protein. Examples of noncoding RNAs include, but are notlimited to, ribosomal RNA, transfer RNA, piwi-interacting RNA, microRNA,siRNA, shRNA, snoRNA, sncRNA, and lncRNA. Pseudogenes may be related toknown genes and are typically no longer expressed. Repeat sequences maycomprise one or more tandem repeats, one or more interspersed repeats,or a combination thereof. Tandem repeats may comprise one or moresatellite DNA, one or more minisatellites, one or more microsatellites,or a combination thereof. Interspersed repeats may comprise one or moretransposons. Transposons may be mobile genetic elements. Mobile geneticelements are often able to change their position within the genome.Transposons may be classified as class I transposable elements (class ITEs) or class II transposable elements (class II TEs). Class I TEs(e.g., retrotransposons) may often copy themselves in two stages, firstfrom DNA to RNA by transcription, then from RNA back to DNA by reversetranscription. The DNA copy may then be inserted into the genome in anew position. Class I TEs may comprise one or more long terminal repeats(LTRs), one or more long interspersed nuclear elements (LINEs), one ormore short interspersed nuclear elements (SINEs), or a combinationthereof. Examples of LTRs include, but are not limited to, humanendogeneous retroviruses (HERVs), medium reiterated repeats 4 (MER4),and retrotransposon. Examples of LINEs include, but are not limited to,LINE1 and LINE2. SINEs may comprise one or more Alu sequences, one ormore mammalian-wide interspersed repeat (MIR), or a combination thereof.Class II TEs (e.g., DNA transposons) often do not involve an RNAintermediate. The DNA transposon is often cut from one site and insertedinto another site in the genome. Alternatively, the DNA transposon isreplicated and inserted into the genome in a new position. Examples ofDNA transposons include, but are not limited to, MER1, MER2, andmariners. Viral elements may comprise one or more endogenous retrovirussequences. Telomeres are often regions of repetitive DNA at the end of achromosome.

The methods disclosed herein may comprise nucleic acid samples orsubsets of nucleic acid molecules comprising one or more genomicregions, wherein at least one of the one or more genomic regionscomprises a genomic region feature comprising an entire exome or portionthereof. The exome is often the part of the genome formed by exons. Theexome may be formed by untranslated regions (UTRs), splice sites and/orintronic regions. The entire exome or portion thereof may comprise oneor more exons of a protein coding gene. The entire exome or portionthereof may comprise one or more untranslated regions (UTRs), splicesites, and introns.

The methods disclosed herein may comprise nucleic acid samples orsubsets of nucleic acid molecules comprising one or more genomicregions, wherein at least one of the one or more genomic regionscomprises a genomic region feature comprising a gene or portion thereof.Typically, a gene comprises stretches of nucleic acids that code for apolypeptide or a functional RNA. A gene may comprise one or more exons,one or more introns, one or more untranslated regions (UTRs), or acombination thereof. Exons are often coding sections of a gene,transcribed into a precursor mRNA sequence, and within the final matureRNA product of the gene. Introns are often noncoding sections of a gene,transcribed into a precursor mRNA sequence, and removed by RNA splicing.UTRs may refer to sections on each side of a coding sequence on a strandof mRNA. A UTR located on the 5′ side of a coding sequence may be calledthe 5′ UTR (or leader sequence). A UTR located on the 3′ side of acoding sequence may be called the 3′ UTR (or trailer sequence). The UTRmay contain one or more elements for controlling gene expression.Elements, such as regulatory elements, may be located in the 5′ UTR.Regulatory sequences, such as a polyadenylation signal, binding sitesfor proteins, and binding sites for miRNAs, may be located in the 3′UTR. Binding sites for proteins located in the 3′ UTR may include, butare not limited to, selenocysteine insertion sequence (SECIS) elementsand AU-rich elements (AREs). SECIS elements may direct a ribosome totranslate the codon UGA as selenocysteine rather than as a stop codon.AREs are often stretches consisting primarily of adenine and uracilnucleotides, which may affect the stability of a mRNA.

The methods disclosed herein may comprise nucleic acid samples orsubsets of nucleic acid molecules comprising one or more genomicregions, wherein at least one of the one or more genomic regionscomprises a genomic region feature comprising a set of genes. The setsof genes may include, but are not limited to, Mendel DB Genes, HumanGene Mutation Database (HGMD) Genes, Cancer Gene Census Genes, OnlineMendelian Inheritance in Man (OMIM) Mendelian Genes, HGMD MendelianGenes, and human leukocyte antigen (HLA) Genes. The set of genes mayhave one or more known Mendelian traits, one or more known diseasetraits, one or more known drug traits, one or more known biomedicallyinterpretable variants, or a combination thereof. A Mendelian trait maybe controlled by a single locus and may show a Mendelian inheritancepattern. A set of genes with known Mendelian traits may comprise one ormore genes encoding Mendelian traits including, but are not limited to,ability to taste phenylthiocarbamide (dominant), ability to smell(bitter almond-like) hydrogen cyanide (recessive), albinism (recessive),brachydactyly (shortness of fingers and toes), and wet (dominant) or dry(recessive) earwax. A disease trait cause or increase risk of diseaseand may be inherited in a Mendelian or complex pattern. A set of geneswith known disease traits may comprise one or more genes encodingdisease traits including, but are not limited to, Cystic Fibrosis,Hemophilia, and Lynch Syndrome. A drug trait may alter metabolism,optimal dose, adverse reactions and side effects of one or more drugs orfamily of drugs. A set of genes with known drug traits may comprise oneor more genes encoding drug traits including, but are not limited to,CYP2D6, UGT1A1 and ADRB1. A biomedically interpretable variant may be apolymorphism in a gene that is associated with a disease or indication.A set of genes with known biomedically interpretable variants maycomprise one or more genes encoding biomedically interpretable variantsincluding, but are not limited to, cystic fibrosis (CF) mutations,muscular dystrophy mutations, p53 mutations, Rb mutations, cell cycleregulators, receptors, and kinases. Alternatively, or additionally, aset of genes with known biomedically interpretable variants may compriseone or more genes associated with Huntington's disease, cancer, cysticfibrosis, muscular dystrophy (e.g., Duchenne muscular dystrophy).

The methods disclosed herein may comprise nucleic acid samples orsubsets of nucleic acid molecules comprising one or more genomicregions, wherein at least one of the one or more genomic regionscomprises a genomic region feature comprising a regulatory element or aportion thereof. Regulatory elements may be cis-regulatory elements ortrans-regulatory elements. Cis-regulatory elements may be sequences thatcontrol transcription of a nearby gene. Cis-regulatory elements may belocated in the 5′ or 3′ untranslated regions (UTRs) or within introns.Trans-regulatory elements may control transcription of a distant gene.Regulatory elements may comprise one or more promoters, one or moreenhancers, or a combination thereof. Promoters may facilitatetranscription of a particular gene and may be found upstream of a codingregion Enhancers may exert distant effects on the transcription level ofa gene.

The methods disclosed herein may comprise nucleic acid samples orsubsets of nucleic acid molecules comprising one or more genomicregions, wherein at least one of the one or more genomic regionscomprises a genomic region feature comprising a polymorphism or aportion thereof. Generally, a polymorphism refers to a mutation in agenotype. A polymorphism may comprise one or more base changes, aninsertion, a repeat, or a deletion of one or more bases. Copy numbervariants (CNVs), transversions and other rearrangements are also formsof genetic variation. Polymorphic markers include restriction fragmentlength polymorphisms, variable number of tandem repeats (VNTR's),hypervariable regions, minisatellites, dinucleotide repeats,trinucleotide repeats, tetranucleotide repeats, simple sequence repeats,and insertion elements such as Alu. The allelic form occurring mostfrequently in a selected population is sometimes referred to as thewildtype form. Diploid organisms may be homozygous or heterozygous forallelic forms. A diallelic polymorphism has two forms. A triallelicpolymorphism has three forms. Single nucleotide polymorphisms (SNPs) area form of polymorphisms. In some aspects of the disclosure, one or morepolymorphisms comprise one or more single nucleotide variations, inDels,small insertions, small deletions, structural variant junctions,variable length tandem repeats, flanking sequences, or a combinationthereof. The one or more polymorphisms may be located within a codingand/or non-coding region. The one or more polymorphisms may be locatedwithin, around, or near a gene, exon, intron, splice site, untranslatedregion, or a combination thereof. The one or more polymorphisms may bemay span at least a portion of a gene, exon, intron, untranslatedregion.

The methods disclosed herein may comprise nucleic acid samples orsubsets of nucleic acid molecules comprising one or more genomicregions, wherein at least one of the one or more genomic regionscomprises a genomic region feature comprising one or more simple tandemrepeats (STRs), unstable expanding repeats, segmental duplications,single and paired read degenerative mapping scores, GRCh37 patches, or acombination thereof. The one or more STRs may comprise one or morehomopolymers, one or more dinucleotide repeats, one or moretrinucleotide repeats, or a combination thereof. The one or morehomopolymers may be about 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18,19, 20 or more bases or base pairs. The dinucleotide repeats and/ortrinucleotide repeats may be about 15, 16, 17, 18, 19, 20, 21, 22, 23,24, 25, 26, 27, 28, 29, 30, 35, 40, 45, 50 or more bases or base pairs.The single and paired read degenerative mapping scores may be based onor derived from alignability of 100mers by GEM from ENCODE/CRG (Guigo),alignability of 75mers by GEM from ENCODE/CRG (Guigo), 100 base pair boxcar average for signal mappability, max of locus and possible pairs forpaired read score, or a combination thereof. The genomic region featuresmay comprise one or more low mean coverage regions from whole genomesequencing (WGS), zero mean coverage regions from WGS, validatedcompressions, or a combination thereof. The low mean coverage regionsfrom WGS may comprise regions generated from Illumina v3 chemistry,regions below the first percentile of Poission distribution based onmean coverage, or a combination thereof. The Zero mean coverage regionsfrom WGS may comprise regions generated from Illumina v3 chemistry. Thevalidated compressions may comprise regions of high mapped depth,regions with two or more observed haplotypes, regions expected to bemissing repeats in a reference, or a combination thereof. The genomicregion features may comprise one or more alternate or non-referencesequences. The one or more alternate or non-reference sequences maycomprise known structural variant junctions, known insertions, knowndeletions, alternate haplotypes, or a combination thereof. The genomicregion features may comprise one or more gene phasing and reassemblygenes. Examples of phasing and reassembly genes include, but are notlimited to, one or more major histocompatibility complexes, bloodtyping, and amaylase gene family. The one or more majorhistocompatibility complexes may comprise one or more HLA Class I, HLAClass II, or a combination thereof. The one or more HLA class I maycomprise HLA-A, HLA-B, HLA-C, or a combination thereof. The one or moreHLA class II may comprise HLA-DP, HLA-DM, HLA-DOA, HLA-DOB, HLA-DQ,HLA-DR, or a combination thereof. The blood typing genes may compriseABO, RHD, RHCE, or a combination thereof.

The methods disclosed herein may comprise nucleic acid samples orsubsets of nucleic acid molecules comprising one or more genomicregions, wherein at least one of the one or more genomic regionscomprises a genomic region feature related to the GC content of one ormore nucleic acid molecules. The GC content may refer to the GC contentof a nucleic acid molecule. Alternatively, the GC content may refer tothe GC content of one or more nucleic acid molecules and may be referredto as the mean GC content. As used herein, the terms “GC content” and“mean GC content” may be used interchangeably. The GC content of agenomic region may be a high GC content. Typically, a high GC contentrefers to a GC content of greater than or equal to about 65%, 70%, 75%,80%, 85%, 90%, 95%, 97%, or more. In some aspects of the disclosure, ahigh GC content may refer to a GC content of greater than or equal toabout 70%. The GC content of a genomic region may be a low GC content.Typically, a low GC content refers to a GC content of less than or equalto about 65%, 60%, 55%, 50%, 45%, 40%, 35%, 30%, 25%, 20%, 15%, 10%, 5%,2%, or less.

The difference in GC content may be used to differentiate two or moregenomic regions or two or more subsets of nucleic acid molecules. Thedifference in GC content may refer to the difference in GC content ofone nucleic acid molecule and another nucleic acid molecule.Alternatively, the difference in GC content may refer to the differencein mean GC content of two or more nucleic acid molecules in a genomicregion from the mean GC content of two or more nucleic acid molecules inanother genomic region. In some aspects of the disclosure, thedifference in GC content refers to the difference in mean GC content oftwo or more nucleic acid molecules in a subset of nucleic acid moleculesfrom the mean GC content of two or more nucleic acid molecules inanother subset of nucleic acid molecules. The difference in GC contentmay be about 5%, 6%, 7%, 8%, 9%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, ormore. In some aspects of the disclosure, the difference in GC content isat least about 5%. The difference in GC content may be at least about10%.

The methods disclosed herein may comprise nucleic acid samples orsubsets of nucleic acid molecules comprising one or more genomicregions, wherein at least one of the one or more genomic regionscomprises a genomic region feature related to the complexity of one ormore nucleic acid molecules. The complexity of a nucleic acid moleculemay refer to the randomness of a nucleotide sequence. Low complexity mayrefer to patterns, repeats and/or depletion of one or more species ofnucleotide in the sequence.

The methods disclosed herein may comprise nucleic acid samples orsubsets of nucleic acid molecules comprising one or more genomicregions, wherein at least one of the one or more genomic regionscomprises a genomic region feature related to the mappablity of one ormore nucleic acid molecules. The mappability of a nucleic acid moleculemay refer to uniqueness of its alignment to a reference sequence. Anucleic acid molecule with low mappability may have poor alignment to areference sequence.

The methods disclosed herein may comprise nucleic acid samples orsubsets of nucleic acid molecules comprising one or more genomic regionscomprising one or more genomic region features. In some aspects of thedisclosure, a single genomic region comprises 1 or more, 2 or more, 3 ormore, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more, 9 or more,10 or more, 11 or more, 12 or more, 13 or more, 14 or more, or 15 ormore genomic region features. The two or more genomic regions maycomprise 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 6 ormore, 7 or more, 8 or more, 9 or more, 10 or more, 11 or more, 12 ormore, 13 or more, 14 or more, 15 or more, 20 or more, 25 or more, 30 ormore, 35 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 ormore, 90 or more, or 100 or more genomic region features. In someaspects of the disclosure, two or more genomic regions comprise 1 ormore, 2 or more, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more,8 or more, 9 or more, 10 or more, 11 or more, 12 or more, 13 or more, 14or more, or 15 or more genomic region features. The one or more genomicregions may comprise 1 or more, 2 or more, 3 or more, 4 or more, 5 ormore, 6 or more, 7 or more, 8 or more, 9 or more, 10 or more, 11 ormore, 12 or more, 13 or more, 14 or more, 15 or more, 20 or more, 25 ormore, 30 or more, 35 or more, 40 or more, 50 or more, 60 or more, 70 ormore, 80 or more, 90 or more, or 100 or more identical or similargenomic region features. Alternatively, or additionally, two or moregenomic regions comprise 1 or more, 2 or more, 3 or more, 4 or more, 5or more, 6 or more, 7 or more, 8 or more, 9 or more, 10 or more, 11 ormore, 12 or more, 13 or more, 14 or more, or 15 or more genomic regionfeatures. The one or more genomic regions may comprise 1 or more, 2 ormore, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more,9 or more, 10 or more, 11 or more, 12 or more, 13 or more, 14 or more,15 or more, 20 or more, 25 or more, 30 or more, 35 or more, 40 or more,50 or more, 60 or more, 70 or more, 80 or more, 90 or more, or 100 ormore different genomic region features.

The methods disclosed herein may comprise nucleic acid samples orsubsets of nucleic acid molecules comprising two or more genomicregions, wherein the two or more genomic regions are differentiateableby one or more genomic region features. The methods disclosed herein maycomprise nucleic acid samples or subsets of nucleic acid moleculescomprising two or more subsets of nucleic acid molecules, wherein thetwo or more subsets of nucleic acid molecules are differentiateable byone or more genomic region features. The two or more genomic regionsand/or the two or more subsets of nucleic acid molecules may bedifferentiateable by 1 or more, 2 or more, 3 or more, 4 or more, 5 ormore, 6 or more, 7 or more, 8 or more, 9 or more, 10 or more, 11 ormore, 12 or more, 13 or more, 14 or more, or 15 or more genomic regionfeatures. The one or more genomic regions may comprise 1 or more, 2 ormore, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more,9 or more, 10 or more, 11 or more, 12 or more, 13 or more, 14 or more,15 or more, 20 or more, 25 or more, or 30 or more genomic regionfeatures.

The methods disclosed herein may comprise nucleic acid samples orsubsets of nucleic acid molecules comprising one or more sets of genomicregions. For example, The methods disclosed herein may comprise nucleicacid samples or subsets of nucleic acid molecules comprising, 1 or more,2 or more, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 ormore, 9 or more, 10 or more, 11 or more, 12 or more, 13 or more, 14 ormore, 15 or more, 20 or more, 25 or more, 30 or more, 35 or more, 40 ormore, 50 or more, 60 or more, 70 or more, 80 or more, 90 or more, or 100or more sets of genomic regions. The one or more sets of genomic regionsmay comprise 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 6 ormore, 7 or more, 8 or more, 9 or more, 10 or more, 11 or more, 12 ormore, 13 or more, 14 or more, 15 or more, 20 or more, 25 or more, 30 ormore, 35 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 ormore, 90 or more, or 100 or more different genomic regions. The one ormore sets of genomic regions may comprise 1 or more, 2 or more, 3 ormore, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more, 9 or more,10 or more, 11 or more, 12 or more, 13 or more, 14 or more, 15 or more,20 or more, 25 or more, 30 or more, 35 or more, 40 or more, 50 or more,60 or more, 70 or more, 80 or more, 90 or more, or 100 or more identicalor similar genomic regions. The one or more sets of genomic regions maycomprise a combination of one or more different genomic regions and oneor more identical or similar genomic regions.

Capture Probes

The methods disclosed herein may comprise one or more capture probes, aplurality of capture probes, or one or more capture probe sets.Typically, the capture probe comprises a nucleic acid binding site. Thecapture probe may further comprise one or more linkers. The captureprobes may further comprise one or more labels. The one or more linkersmay attach the one or more labels to the nucleic acid binding site.

The methods disclosed herein may comprise 1 or more, 2 or more, 3 ormore, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more, 9 or more,10 or more, 20 or more, 30 or more, 40 or more, 50 or more, 60 or more,70 or more, 80 or more, 90 or more, 100 or more, 125 or more, 150 ormore, 175 or more, 200 or more, 250 or more, 300 or more, 350 or more,400 or more, 500 or more, 600 or more, 700 or more, 800 or more, 900 ormore, or 1000 or more one or more capture probes or capture probe sets.The one or more capture probes or capture probe sets may be different,similar, identical, or a combination thereof.

The one or more capture probe may comprise a nucleic acid binding sitethat hybridizes to at least a portion of the one or more nucleic acidmolecules or variant or derivative thereof in the sample or subset ofnucleic acid molecules. The capture probes may comprise a nucleic acidbinding site that hybridizes to one or more genomic regions. The captureprobes may hybridize to different, similar, and/or identical genomicregions. The one or more capture probes may be at least about 50%, 55%,60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 97%, 99% or more complementaryto the one or more nucleic acid molecules or variant or derivativethereof.

The capture probes may comprise one or more nucleotides. The captureprobes may comprise 1 or more, 2 or more, 3 or more, 4 or more, 5 ormore, 6 or more, 7 or more, 8 or more, 9 or more, 10 or more, 20 ormore, 30 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 ormore, 90 or more, 100 or more, 125 or more, 150 or more, 175 or more,200 or more, 250 or more, 300 or more, 350 or more, 400 or more, 500 ormore, 600 or more, 700 or more, 800 or more, 900 or more, or 1000 ormore nucleotides. The capture probes may comprise about 100 nucleotides.The capture probes may comprise between about 10 to about 500nucleotides, between about 20 to about 450 nucleotides, between about 30to about 400 nucleotides, between about 40 to about 350 nucleotides,between about 50 to about 300 nucleotides, between about 60 to about 250nucleotides, between about 70 to about 200 nucleotides, or between about80 to about 150 nucleotides. In some aspects of the disclosure, thecapture probes comprise between about 80 nucleotides to about 100nucleotides.

The plurality of capture probes or the capture probe sets may comprisetwo or more capture probes with identical, similar, and/or differentnucleic acid binding site sequences, linkers, and/or labels. Forexample, two or more capture probes comprise identical nucleic acidbinding sites. In another example, two or more capture probes comprisesimilar nucleic acid binding sites. In yet another example, two or morecapture probes comprise different nucleic acid binding sites. The two ormore capture probes may further comprise one or more linkers. The two ormore capture probes may further comprise different linkers. The two ormore capture probes may further comprise similar linkers. The two ormore capture probes may further comprise identical linkers. The two ormore capture probes may further comprise one or more labels. The two ormore capture probes may further comprise different labels. The two ormore capture probes may further comprise similar labels. The two or morecapture probes may further comprise identical labels.

Assays and Techniques

The methods disclosed herein may comprise producing one or more subsetsof nucleic acid molecules from a nucleic acid sample. The methodsdisclosed herein may comprise producing 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,11, 12, 13, 14, 15 or more subsets of nucleic acid molecules from anucleic acid sample. The one or more subsets of nucleic acid moleculesmay be produced by contacting a nucleic acid sample with one or morebeads, capture probes, labels, or a combination thereof. Alternatively,or additionally, the one or more subsets of nucleic acid molecules areproduced by separating at least one nucleic acid molecule from anothernucleic acid molecule.

The methods disclosed herein may comprise producing two or more subsetsof nucleic acids may by contacting a nucleic acid sample with one ormore beads to produce a first subset of nucleic acid moleculescomprising one or more bead bound nucleic acid molecules and a secondsubset of nucleic acid molecules comprising one or more bead freenucleic acid molecules.

Alternatively, or additionally, methods disclosed herein may compriseproducing two or more subsets of nucleic acids may by contacting thenucleic acid sample with one or more capture probes to produce a firstsubset of nucleic acid molecules comprising one or more capture probehybridized nucleic acid molecules and a second subset of nucleic acidmolecules comprising one or more capture probe free nucleic acidmolecules.

In some aspects of the disclosure, producing the two or more subsets ofnucleic acids comprises contacting the nucleic acid sample with one ormore labels to produce a first subset of nucleic acid moleculescomprising one or more labeled nucleic acid molecules and a secondsubset of nucleic acid molecules comprising one or more non-labelednucleic acid molecules.

Producing the two or more subsets of nucleic acids comprises contactingthe nucleic acid sample with one or more capture probes to produce afirst subset of nucleic acid molecules comprising one or more captureprobe hybridized nucleic acid molecules and a second subset of nucleicacid molecules comprising one or more capture probe free nucleic acidmolecules.

The methods disclosed herein may comprise conducting one or more assayson a sample comprising one or more nucleic acid molecules. Producing twoor more subsets of nucleic acid molecules may comprise conducting one ormore assays. The assays may be conducted on a subset of nucleic acidmolecules from the sample. The assays maybe conducted on one or morenucleic acids molecules from the sample. The assays may be conducted onat least a portion of a subset of nucleic acid molecules. The assays maycomprise one or more techniques, reagents, capture probes, primers,labels, and/or components for the detection, quantification, and/oranalysis of one or more nucleic acid molecules.

The methods disclosed herein may comprise conducting one or more assayson two or more subsets of nucleic acid molecules. The methods disclosedherein may further comprise combining at least a portion of two or moresubsets of nucleic acid molecules to produce a combined subset ofnucleic acid molecules and conducting at least one assay on the combinedsubset of nucleic acid molecules. In some aspects of the disclosure, twoor more subsets of nucleic acid molecules may be produced by one or moremethods disclosed herein,

Assays may include, but are not limited to, sequencing, amplification,hybridization, enrichment, isolation, elution, fragmentation, detection,quantification of one or more nucleic acid molecules. Assays may includemethods for preparing one or more nucleic acid molecules.

The methods disclosed herein may comprise conducting one or moresequencing reactions on one or more nucleic acid molecules in a sample.The methods disclosed herein may comprise conducting 1 or more, 2 ormore, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more,9 or more, 10 or more, 15 or more, 20 or more, 30 or more, 40 or more,50 or more, 60 or more, 70 or more, 80 or more, 90 or more, 100 or more,200 or more, 300 or more, 400 or more, 500 or more, 600 or more, 700 ormore, 800 or more, 900 or more, or 1000 or more sequencing reactions onone or more nucleic acid molecules in a sample. The sequencing reactionsmay be run simultaneously, sequentially, or a combination thereof. Thesequencing reactions may comprise whole genome sequencing or exomesequencing. The sequencing reactions may comprise Maxim-Gilbert,chain-termination or high-throughput systems. Alternatively, oradditionally, the sequencing reactions may comprise Helioscope™ singlemolecule sequencing, Nanopore DNA sequencing, Lynx Therapeutics'Massively Parallel Signature Sequencing (MPSS), 454 pyrosequencing,Single Molecule real time (RNAP) sequencing, Illumina (Solexa)sequencing, SOLiD sequencing, Ion Torrent™, Ion semiconductorsequencing, Single Molecule SMRT™ sequencing, Polony sequencing, DNAnanoball sequencing, VisiGen Biotechnologies approach, or a combinationthereof. Alternatively, or additionally, the sequencing reactions cancomprise one or more sequencing platforms, including, but not limitedto, Genome Analyzer IIx, HiSeq, and MiSeq offered by Illumina, SingleMolecule Real Time (SMRT™) technology, such as the PacBio RS systemoffered by Pacific Biosciences (California) and the Solexa Sequencer,True Single Molecule Sequencing (tSMS™) technology such as theHeliScope™ Sequencer offered by Helicos Inc. (Cambridge, Mass.).Sequencing reactions may also comprise electron microscopy or achemical-sensitive field effect transistor (chemFET) array. In someaspects of the disclosure, sequencing reactions comprise capillarysequencing, next generation sequencing, Sanger sequencing, sequencing bysynthesis, sequencing by ligation, sequencing by hybridization, singlemolecule sequencing, or a combination thereof. Sequencing by synthesismay comprise reversible terminator sequencing, processive singlemolecule sequencing, sequential flow sequencing, or a combinationthereof. Sequential flow sequencing may comprise pyrosequencing,pH-mediated sequencing, semiconductor sequencing, or a combinationthereof.

The methods disclosed herein may comprise conducting at least one longread sequencing reaction and at least one short read sequencingreaction. The long read sequencing reaction and/or short read sequencingreaction may be conducted on at least a portion of a subset of nucleicacid molecules. The long read sequencing reaction and/or short readsequencing reaction may be conducted on at least a portion of two ormore subsets of nucleic acid molecules. Both a long read sequencingreaction and a short read sequencing reaction may be conducted on atleast a portion of one or more subsets of nucleic acid molecules.

Sequencing of the one or more nucleic acid molecules or subsets thereofmay comprise at least about 5; 10; 15; 20; 25; 30; 35; 40; 45; 50; 60;70; 80; 90; 100; 200; 300; 400; 500; 600; 700; 800; 900; 1,000; 1500;2,000; 2500; 3,000; 3500; 4,000; 4500; 5,000; 5500; 6,000; 6500; 7,000;7500; 8,000; 8500; 9,000; 10,000; 25,000; 50,000; 75,000; 100,000;250,000; 500,000; 750,000; 10,000,000; 25,000,000; 50,000,000;100,000,000; 250,000,000; 500,000,000; 750,000,000; 1,000,000,000 ormore sequencing reads.

Sequencing reactions may comprise sequencing at least about 50; 60; 70;80; 90; 100; 110; 120; 130; 140; 150; 160; 170; 180; 190; 200; 210; 220;230; 240; 250; 260; 270; 280; 290; 300; 325; 350; 375; 400; 425; 450;475; 500; 600; 700; 800; 900; 1,000; 1500; 2,000; 2500; 3,000; 3500;4,000; 4500; 5,000; 5500; 6,000; 6500; 7,000; 7500; 8,000; 8500; 9,000;10,000; 20,000; 30,000; 40,000; 50,000; 60,000; 70,000; 80,000; 90,000;100,000 or more bases or base pairs of one or more nucleic acidmolecules. Sequencing reactions may comprise sequencing at least about50; 60; 70; 80; 90; 100; 110; 120; 130; 140; 150; 160; 170; 180; 190;200; 210; 220; 230; 240; 250; 260; 270; 280; 290; 300; 325; 350; 375;400; 425; 450; 475; 500; 600; 700; 800; 900; 1,000; 1500; 2,000; 2500;3,000; 3500; 4,000; 4500; 5,000; 5500; 6,000; 6500; 7,000; 7500; 8,000;8500; 9,000; 10,000; 20,000; 30,000; 40,000; 50,000; 60,000; 70,000;80,000; 90,000; 100,000 or more consecutive bases or base pairs of oneor more nucleic acid molecules.

Preferably, the sequencing techniques used in the methods of theinvention generates at least 100 reads per run, at least 200 reads perrun, at least 300 reads per run, at least 400 reads per run, at least500 reads per run, at least 600 reads per run, at least 700 reads perrun, at least 800 reads per run, at least 900 reads per run, at least1000 reads per run, at least 5,000 reads per run, at least 10,000 readsper run, at least 50,000 reads per run, at least 100,000 reads per run,at least 500,000 reads per run, or at least 1,000,000 reads per run.Alternatively, the sequencing technique used in the methods of theinvention generates at least 1,500,000 reads per run, at least 2,000,000reads per run, at least 2,500,000 reads per run, at least 3,000,000reads per run, at least 3,500,000 reads per run, at least 4,000,000reads per run, at least 4,500,000 reads per run, or at least 5,000,000reads per run.

Preferably, the sequencing techniques used in the methods of theinvention can generate at least about 30 base pairs, at least about 40base pairs, at least about 50 base pairs, at least about 60 base pairs,at least about 70 base pairs, at least about 80 base pairs, at leastabout 90 base pairs, at least about 100 base pairs, at least about 110,at least about 120 base pairs per read, at least about 150 base pairs,at least about 200 base pairs, at least about 250 base pairs, at leastabout 300 base pairs, at least about 350 base pairs, at least about 400base pairs, at least about 450 base pairs, at least about 500 basepairs, at least about 550 base pairs, at least about 600 base pairs, atleast about 700 base pairs, at least about 800 base pairs, at leastabout 900 base pairs, or at least about 1,000 base pairs per read.Alternatively, the sequencing technique used in the methods of theinvention can generate long sequencing reads. In some instances, thesequencing technique used in the methods of the invention can generateat least about 1,200 base pairs per read, at least about 1,500 basepairs per read, at least about 1,800 base pairs per read, at least about2,000 base pairs per read, at least about 2,500 base pairs per read, atleast about 3,000 base pairs per read, at least about 3,500 base pairsper read, at least about 4,000 base pairs per read, at least about 4,500base pairs per read, at least about 5,000 base pairs per read, at leastabout 6,000 base pairs per read, at least about 7,000 base pairs perread, at least about 8,000 base pairs per read, at least about 9,000base pairs per read, at least about 10,000 base pairs per read, 20,000base pairs per read, 30,000 base pairs per read, 40,000 base pairs perread, 50,000 base pairs per read, 60,000 base pairs per read, 70,000base pairs per read, 80,000 base pairs per read, 90,000 base pairs perread, or 100,000 base pairs per read.

High-throughput sequencing systems may allow detection of a sequencednucleotide immediately after or upon its incorporation into a growingstrand, i.e., detection of sequence in real time or substantially realtime. In some cases, high throughput sequencing generates at least1,000, at least 5,000, at least 10,000, at least 20,000, at least30,000, at least 40,000, at least 50,000, at least 100,000 or at least500,000 sequence reads per hour; with each read being at least 50, atleast 60, at least 70, at least 80, at least 90, at least 100, at least120, at least 150, at least 200, at least 250, at least 300, at least350, at least 400, at least 450, or at least 500 bases per read.Sequencing can be performed using nucleic acids described herein such asgenomic DNA, cDNA derived from RNA transcripts or RNA as a template.

The methods disclosed herein may comprise conducting one or moreamplification reactions on one or more nucleic acid molecules in asample. The term “amplification” refers to any process of producing atleast one copy of a nucleic acid molecule. The terms “amplicons” and“amplified nucleic acid molecule” refer to a copy of a nucleic acidmolecule and can be used interchangeably. The amplification reactionscan comprise PCR-based methods, non-PCR based methods, or a combinationthereof. Examples of non-PCR based methods include, but are not limitedto, multiple displacement amplification (MDA), transcription-mediatedamplification (TMA), nucleic acid sequence-based amplification (NASBA),strand displacement amplification (SDA), real-time SDA, rolling circleamplification, or circle-to-circle amplification. PCR-based methods mayinclude, but are not limited to, PCR, HD-PCR, Next Gen PCR, digital RTA,or any combination thereof. Additional PCR methods include, but are notlimited to, linear amplification, allele-specific PCR, Alu PCR, assemblyPCR, asymmetric PCR, droplet PCR, emulsion PCR, helicase dependentamplification HDA, hot start PCR, inverse PCR,linear-after-the-exponential (LATE)-PCR, long PCR, multiplex PCR, nestedPCR, hemi-nested PCR, quantitative PCR, RT-PCR, real time PCR, singlecell PCR, and touchdown PCR.

The methods disclosed herein may comprise conducting one or morehybridization reactions on one or more nucleic acid molecules in asample. The hybridization reactions may comprise the hybridization ofone or more capture probes to one or more nucleic acid molecules in asample or subset of nucleic acid molecules. The hybridization reactionsmay comprise hybridizing one or more capture probe sets to one or morenucleic acid molecules in a sample or subset of nucleic acid molecules.The hybridization reactions may comprise one or more hybridizationarrays, multiplex hybridization reactions, hybridization chainreactions, isothermal hybridization reactions, nucleic acidhybridization reactions, or a combination thereof. The one or morehybridization arrays may comprise hybridization array genotyping,hybridization array proportional sensing, DNA hybridization arrays,macroarrays, microarrays, high-density oligonucleotide arrays, genomichybridization arrays, comparative hybridization arrays, or a combinationthereof. The hybridization reaction may comprise one or more captureprobes, one or more beads, one or more labels, one or more subsets ofnucleic acid molecules, one or more nucleic acid samples, one or morereagents, one or more wash buffers, one or more elution buffers, one ormore hybridization buffers, one or more hybridization chambers, one ormore incubators, one or more separators, or a combination thereof.

The methods disclosed herein may comprise conducting one or moreenrichment reactions on one or more nucleic acid molecules in a sample.The enrichment reactions may comprise contacting a sample with one ormore beads or bead sets. The enrichment reaction may comprisedifferential amplification of two or more subsets of nucleic acidmolecules based on one or more genomic region features. For example, theenrichment reaction comprises differential amplification of two or moresubsets of nucleic acid molecules based on GC content. Alternatively, oradditionally, the enrichment reaction comprises differentialamplification of two or more subsets of nucleic acid molecules based onmethylation state. The enrichment reactions may comprise one or morehybridization reactions. The enrichment reactions may further compriseisolation and/or purification of one or more hybridized nucleic acidmolecules, one or more bead bound nucleic acid molecules, one or morefree nucleic acid molecules (e.g., capture probe free nucleic acidmolecules, bead free nucleic acid molecules), one or more labelednucleic acid molecules, one or more non-labeled nucleic acid molecules,one or more amplicons, one or more non-amplified nucleic acid molecules,or a combination thereof. Alternatively, or additionally, the enrichmentreaction may comprise enriching for one or more cell types in thesample. The one or more cell types may be enriched by flow cytometry.

The one or more enrichment reactions may produce one or more enrichednucleic acid molecules. The enriched nucleic acid molecules may comprisea nucleic acid molecule or variant or derivative thereof. For example,the enriched nucleic acid molecules comprise one or more hybridizednucleic acid molecules, one or more bead bound nucleic acid molecules,one or more free nucleic acid molecules (e.g., capture probe freenucleic acid molecules, bead free nucleic acid molecules), one or morelabeled nucleic acid molecules, one or more non-labeled nucleic acidmolecules, one or more amplicons, one or more non-amplified nucleic acidmolecules, or a combination thereof. The enriched nucleic acid moleculesmay be differentiated from non-enriched nucleic acid molecules by GCcontent, molecular size, genomic regions, genomic region features, or acombination thereof. The enriched nucleic acid molecules may be derivedfrom one or more assays, supernatants, eluants, or a combinationthereof. The enriched nucleic acid molecules may differ from thenon-enriched nucleic acid molecules by mean size, mean GC content,genomic regions, or a combination thereof.

The methods disclosed herein may comprise conducting one or moreisolation or purification reactions on one or more nucleic acidmolecules in a sample. The isolation or purification reactions maycomprise contacting a sample with one or more beads or bead sets. Theisolation or purification reaction may comprise one or morehybridization reactions, enrichment reactions, amplification reactions,sequencing reactions, or a combination thereof. The isolation orpurification reaction may comprise the use of one or more separators.The one or more separators may comprise a magnetic separator. Theisolation or purification reaction may comprise separating bead boundnucleic acid molecules from bead free nucleic acid molecules. Theisolation or purification reaction may comprise separating capture probehybridized nucleic acid molecules from capture probe free nucleic acidmolecules. The isolation or purification reaction may compriseseparating a first subset of nucleic acid molecules from a second subsetof nucleic acid molecules, wherein the first subset of nucleic acidmolecules differ from the second subset on nucleic acid molecules bymean size, mean GC content, genomic regions, or a combination thereof.

The methods disclosed herein may comprise conducting one or more elutionreactions on one or more nucleic acid molecules in a sample. The elutionreactions may comprise contacting a sample with one or more beads orbead sets. The elution reaction may comprise separating bead boundnucleic acid molecules from bead free nucleic acid molecules. Theelution reaction may comprise separating capture probe hybridizednucleic acid molecules from capture probe free nucleic acid molecules.The elution reaction may comprise separating a first subset of nucleicacid molecules from a second subset of nucleic acid molecules, whereinthe first subset of nucleic acid molecules differ from the second subseton nucleic acid molecules by mean size, mean GC content, genomicregions, or a combination thereof.

The methods disclosed herein may comprise one or more fragmentationreactions. The fragmentation reactions may comprise fragmenting one ormore nucleic acid molecules in a sample or subset of nucleic acidmolecules to produce one or more fragmented nucleic acid molecules. Theone or more nucleic acid molecules may be fragmented by sonication,needle shear, nebulisation, shearing (e.g., acoustic shearing,mechanical shearing, point-sink shearing), passage through a Frenchpressure cell, or enzymatic digestion. Enzymatic digestion may occur bynuclease digestion (e.g., micrococcal nuclease digestion, endonucleases,exonucleases, RNAse H or DNase I). Fragmentation of the one or morenucleic acid molecules may result in fragment sized of about 100 basepairs to about 2000 base pairs, about 200 base pairs to about 1500 basepairs, about 200 base pairs to about 1000 base pairs, about 200 basepairs to about 500 base pairs, about 500 base pairs to about 1500 basepairs, and about 500 base pairs to about 1000 base pairs. The one ormore fragmentation reactions may result in fragment sized of about 50base pairs to about 1000 base pairs. The one or more fragmentationreactions may result in fragment sized of about 100 base pairs, 150 basepairs, 200 base pairs, 250 base pairs, 300 base pairs, 350 base pairs,400 base pairs, 450 base pairs, 500 base pairs, 550 base pairs, 600 basepairs, 650 base pairs, 700 base pairs, 750 base pairs, 800 base pairs,850 base pairs, 900 base pairs, 950 base pairs, 1000 base pairs or more.

Fragmenting the one or more nucleic acid molecules may comprisemechanical shearing of the one or more nucleic acid molecules in thesample for a period of time. The fragmentation reaction may occur for atleast about 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80,85, 90, 95, 100, 125, 150, 175, 200, 225, 250, 275, 300, 325, 350, 375,400, 425, 450, 475, 500 or more seconds.

Fragmenting the one or more nucleic acid molecules may comprisecontacting a nucleic acid sample with one or more beads. Fragmenting theone or more nucleic acid molecules may comprise contacting the nucleicacid sample with a plurality of beads, wherein the ratio of the volumeof the plurality of beads to the volume of nucleic acid sample is about0.10, 0.20, 0.30, 0.40, 0.50, 0.60, 0.70, 0.80, 0.90, 1.00, 1.10, 1.20,1.30, 1.40, 1.50, 1.60, 1.70, 1.80, 1.90, 2.00 or more. Fragmenting theone or more nucleic acid molecules may comprise contacting the nucleicacid sample with a plurality of beads, wherein the ratio of the volumeof the plurality of beads to the volume of nucleic acid is about 2.00,1.90, 1.80, 1.70, 1.60, 1.50, 1.40, 1.30, 1.20, 1.10, 1.00, 0.90, 0.80,0.70, 0.60, 0.50, 0.40, 0.30, 0.20, 0.10, 0.05, 0.04, 0.03, 0.02, 0.01or less.

The methods disclosed herein may comprise conducting one or moredetection reactions on one or more nucleic acid molecules in a sample.Detection reactions may comprise one or more sequencing reactions.Alternatively, conducting a detection reaction comprises opticalsensing, electrical sensing, or a combination thereof. Optical sensingmay comprise optical sensing of a photoilluminscence photon emission,fluorescence photon emission, pyrophosphate photon emission,chemiluminescence photon emission, or a combination thereof. Electricalsensing may comprise electrical sensing of an ion concentration, ioncurrent modulation, nucleotide electrical field, nucleotide tunnelingcurrent, or a combination thereof.

The methods disclosed herein may comprise conducting one or morequantification reactions on one or more nucleic acid molecules in asample. Quantification reactions may comprise sequencing, PCR, qPCR,digital PCR, or a combination thereof.

The methods disclosed herein may comprise one or more samples. Themethods disclosed herein may comprise 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,12, 13, 14, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85,90, 95, 100 or more samples. The sample may be derived from a subject.The two or more samples may be derived from a single subject. The two ormore samples may be derived from t2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,13, 14, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90,95, 100 or more different subjects. The subject may be a mammal,reptiles, amphibians, avians, and fish. The mammal may be a human, ape,orangutan, monkey, chimpanzee, cow, pig, horse, rodent, bird, reptile,dog, cat, or other animal. A reptile may be a lizard, snake, alligator,turtle, crocodile, and tortoise. An amphibian may be a toad, frog, newt,and salamander. Examples of avians include, but are not limited to,ducks, geese, penguins, ostriches, and owls. Examples of fish include,but are not limited to, catfish, eels, sharks, and swordfish.Preferably, the subject is a human. The subject may suffer from adisease or condition.

The two or more samples may be collected over 1, 2, 3, 4, 5, 6, 7, 8, 9,10, 11, 12, 15, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500,600, 700, 800, 900, 1000 or time points. The time points may occur overa 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20,21, 22, 23, 24, 25, 30, 35, 40, 45, 50, 55, 60 or more hour period. Thetime points may occur over a 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50, 55,60 or more day period. The time points may occur over a 1, 2, 3, 4, 5,6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24,25, 30, 35, 40, 45, 50, 55, 60 or more week period. The time points mayoccur over a 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50, 55, 60 or more monthperiod. The time points may occur over a 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40,45, 50, 55, 60 or more year period.

The sample may be from a body fluid, cell, skin, tissue, organ, orcombination thereof. The sample may be a blood, plasma, a bloodfraction, saliva, sputum, urine, semen, transvaginal fluid,cerebrospinal fluid, stool, a cell or a tissue biopsy. The sample may befrom an adrenal gland, appendix, bladder, brain, ear, esophagus, eye,gall bladder, heart, kidney, large intestine, liver, lung, mouth,muscle, nose, pancreas, parathyroid gland, pineal gland, pituitarygland, skin, small intestine, spleen, stomach, thymus, thyroid gland,trachea, uterus, vermiform appendix, cornea, skin, heart valve, artery,or vein

The samples may comprise one or more nucleic acid molecules. The nucleicacid molecule may be a DNA molecule, RNA molecule (e.g. mRNA, cRNA ormiRNA), and DNA/RNA hybrids. Examples of DNA molecules include, but arenot limited to, double-stranded DNA, single-stranded DNA,single-stranded DNA hairpins, cDNA, genomic DNA. The nucleic acid may bean RNA molecule, such as a double-stranded RNA, single-stranded RNA,ncRNA, RNA hairpin, and mRNA. Examples of ncRNA include, but are notlimited to, siRNA, miRNA, snoRNA, piRNA, tiRNA, PASR, TASR, aTASR,TSSa-RNA, snRNA, RE-RNA, uaRNA, x-ncRNA, hY RNA, usRNA, snaR, and vtRNA.

The methods disclosed herein may comprise one or more containers. Themethods disclosed herein may comprise 1 or more, 2 or more, 3 or more, 4or more, 5 or more, 6 or more, 7 or more, 8 or more, 9 or more, 10 ormore, 20 or more, 30 or more, 40 or more, 50 or more, 60 or more, 70 ormore, 80 or more, 90 or more, 100 or more, 125 or more, 150 or more, 175or more, 200 or more, 250 or more, 300 or more, 350 or more, 400 ormore, 500 or more, 600 or more, 700 or more, 800 or more, 900 or more,or 1000 or more containers. The one or more containers may be different,similar, identical, or a combination thereof. Examples of containersinclude, but are not limited to, plates, microplates, PCR plates, wells,microwells, tubes, Eppendorf tubes, vials, arrays, microarrays, andchips.

The methods disclosed herein may comprise one or more reagents. Themethods disclosed herein may comprise 1 or more, 2 or more, 3 or more, 4or more, 5 or more, 6 or more, 7 or more, 8 or more, 9 or more, 10 ormore, 20 or more, 30 or more, 40 or more, 50 or more, 60 or more, 70 ormore, 80 or more, 90 or more, 100 or more, 125 or more, 150 or more, 175or more, 200 or more, 250 or more, 300 or more, 350 or more, 400 ormore, 500 or more, 600 or more, 700 or more, 800 or more, 900 or more,or 1000 or more reagents. The one or more reagents may be different,similar, identical, or a combination thereof. The reagents may improvethe efficiency of the one or more assays. Reagents may improve thestability of the nucleic acid molecule or variant or derivative thereof.Reagents may include, but are not limited to, enzymes, proteases,nucleases, molecules, polymerases, reverse transcriptases, ligases, andchemical compounds. The methods disclosed herein may comprise conductingan assay comprising one or more antioxidants. Generally, antioxidantsare molecules that inhibit oxidation of another molecule. Examples ofantioxidants include, but are not limited to, ascorbic acid (e.g.,vitamin C), glutathione, lipoic acid, uric acid, carotenes, α-tocopherol(e.g., vitamin E), ubiquinol (e.g., coenzyme Q), and vitamin A.

The methods disclosed herein may comprise one or more buffers orsolutions. The methods disclosed herein may comprise 1 or more, 2 ormore, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more,9 or more, 10 or more, 20 or more, 30 or more, 40 or more, 50 or more,60 or more, 70 or more, 80 or more, 90 or more, 100 or more, 125 ormore, 150 or more, 175 or more, 200 or more, 250 or more, 300 or more,350 or more, 400 or more, 500 or more, 600 or more, 700 or more, 800 ormore, 900 or more, or 1000 or more buffers or solutions. The one or morebuffers or solutions may be different, similar, identical, or acombination thereof. The buffers or solutions may improve the efficiencyof the one or more assays. Buffers or solutions may improve thestability of the nucleic acid molecule or variant or derivative thereof.Buffers or solutions may include, but are not limited to, wash buffers,elution buffers, and hybridization buffers.

The methods disclosed herein may comprise one or more beads, a pluralityof beads, or one or more bead sets. The methods disclosed herein maycomprise 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 6 ormore, 7 or more, 8 or more, 9 or more, 10 or more, 20 or more, 30 ormore, 40 or more, 50 or more, 60 or more, 70 or more, 80 or more, 90 ormore, 100 or more, 125 or more, 150 or more, 175 or more, 200 or more,250 or more, 300 or more, 350 or more, 400 or more, 500 or more, 600 ormore, 700 or more, 800 or more, 900 or more, or 1000 or more one or morebeads or bead sets. The one or more beads or bead sets may be different,similar, identical, or a combination thereof. The beads may be magnetic,antibody coated, protein A crosslinked, protein G crosslinked,streptavidin coated, oligonucleotide conjugated, silica coated, or acombination thereof. Examples of beads include, but are not limited to,Ampure beads, AMPure XP beads, streptavidin beads, agarose beads,magnetic beads, Dynabeads®, MACS® microbeads, antibody conjugated beads(e.g., anti-immunoglobulin microbead), protein A conjugated beads,protein G conjugated beads, protein A/G conjugated beads, protein Lconjugated beads, oligo-dT conjugated beads, silica beads, silica-likebeads, anti-biotin microbead, anti-fluorochrome microbead, and BcMag™Carboxy-Terminated Magnetic Beads. In some aspects of the disclosure,the one or more beads comprise one or more Ampure beads. Alternatively,or additionally, the one or more beads comprise AMPure XP beads.

The methods disclosed herein may comprise one or more primers, aplurality of primers, or one or more primer sets. The primers mayfurther comprise one or more linkers. The primers may further compriseor more labels. The primers may be used in one or more assays. Forexample, the primers are used in one or more sequencing reactions,amplification reactions, or a combination thereof. The methods disclosedherein may comprise 1 or more, 2 or more, 3 or more, 4 or more, 5 ormore, 6 or more, 7 or more, 8 or more, 9 or more, 10 or more, 20 ormore, 30 or more, 40 or more, 50 or more, 60 or more, 70 or more, 80 ormore, 90 or more, 100 or more, 125 or more, 150 or more, 175 or more,200 or more, 250 or more, 300 or more, 350 or more, 400 or more, 500 ormore, 600 or more, 700 or more, 800 or more, 900 or more, or 1000 ormore one or more primers or primer sets. The primers may comprise about100 nucleotides. The primers may comprise between about 10 to about 500nucleotides, between about 20 to about 450 nucleotides, between about 30to about 400 nucleotides, between about 40 to about 350 nucleotides,between about 50 to about 300 nucleotides, between about 60 to about 250nucleotides, between about 70 to about 200 nucleotides, or between about80 to about 150 nucleotides. In some aspects of the disclosure, theprimers comprise between about 80 nucleotides to about 100 nucleotides.The one or more primers or primer sets may be different, similar,identical, or a combination thereof.

The primers may hybridize to at least a portion of the one or morenucleic acid molecules or variant or derivative thereof in the sample orsubset of nucleic acid molecules. The primers may hybridize to one ormore genomic regions. The primers may hybridize to different, similar,and/or identical genomic regions. The one or more primers may be atleast about 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, 97%, 99%or more complementary to the one or more nucleic acid molecules orvariant or derivative thereof.

The primers may comprise one or more nucleotides. The primers maycomprise 1 or more, 2 or more, 3 or more, 4 or more, 5 or more, 6 ormore, 7 or more, 8 or more, 9 or more, 10 or more, 20 or more, 30 ormore, 40 or more, 50 or more, 60 or more, 70 or more, 80 or more, 90 ormore, 100 or more, 125 or more, 150 or more, 175 or more, 200 or more,250 or more, 300 or more, 350 or more, 400 or more, 500 or more, 600 ormore, 700 or more, 800 or more, 900 or more, or 1000 or morenucleotides. The primers may comprise about 100 nucleotides. The primersmay comprise between about 10 to about 500 nucleotides, between about 20to about 450 nucleotides, between about 30 to about 400 nucleotides,between about 40 to about 350 nucleotides, between about 50 to about 300nucleotides, between about 60 to about 250 nucleotides, between about 70to about 200 nucleotides, or between about 80 to about 150 nucleotides.In some aspects of the disclosure, the primers comprise between about 80nucleotides to about 100 nucleotides.

The plurality of primers or the primer sets may comprise two or moreprimers with identical, similar, and/or different sequences, linkers,and/or labels. For example, two or more primers comprise identicalsequences. In another example, two or more primers comprise similarsequences. In yet another example, two or more primers comprisedifferent sequences. The two or more primers may further comprise one ormore linkers. The two or more primers may further comprise differentlinkers. The two or more primers may further comprise similar linkers.The two or more primers may further comprise identical linkers. The twoor more primers may further comprise one or more labels. The two or moreprimers may further comprise different labels. The two or more primersmay further comprise similar labels. The two or more primers may furthercomprise identical labels.

The capture probes, primers, labels, and/or beads may comprise one ormore nucleotides. The one or more nucleotides may comprise RNA, DNA, amix of DNA and RNA residues or their modified analogs such as 2′-OMe, or2′-fluoro (2′-F), locked nucleic acid (LNA), or abasic sites.

The methods disclosed herein may comprise one or more labels. Themethods disclosed herein may comprise 1 or more, 2 or more, 3 or more, 4or more, 5 or more, 6 or more, 7 or more, 8 or more, 9 or more, 10 ormore, 20 or more, 30 or more, 40 or more, 50 or more, 60 or more, 70 ormore, 80 or more, 90 or more, 100 or more, 125 or more, 150 or more, 175or more, 200 or more, 250 or more, 300 or more, 350 or more, 400 ormore, 500 or more, 600 or more, 700 or more, 800 or more, 900 or more,or 1000 or more one or more labels. The one or more labels may bedifferent, similar, identical, or a combination thereof.

Examples of labels include, but are not limited to, chemical,biochemical, biological, colorimetric, enzymatic, fluorescent, andluminescent labels, which are well known in the art. The label comprisea dye, a photocrosslinker, a cytotoxic compound, a drug, an affinitylabel, a photoaffinity label, a reactive compound, an antibody orantibody fragment, a biomaterial, a nanoparticle, a spin label, afluorophore, a metal-containing moiety, a radioactive moiety, a novelfunctional group, a group that covalently or noncovalently interactswith other molecules, a photocaged moiety, an actinic radiationexcitable moiety, a ligand, a photoisomerizable moiety, biotin, a biotinanalogue, a moiety incorporating a heavy atom, a chemically cleavablegroup, a photocleavable group, a redox-active agent, an isotopicallylabeled moiety, a biophysical probe, a phosphorescent group, achemiluminescent group, an electron dense group, a magnetic group, anintercalating group, a chromophore, an energy transfer agent, abiologically active agent, a detectable label, or a combination thereof.

The label may be a chemical label. Examples of chemical labels caninclude, but are not limited to, biotin and radiosiotypes (e.g., iodine,carbon, phosphate, hydrogen).

The methods, kits, and compositions disclosed herein may comprise abiological label. The biological labels may comprise metabolic labels,including, but not limited to, bioorthogonal azide-modified amino acids,sugars, and other compounds.

The methods, kits, and compositions disclosed herein may comprise anenzymatic label. Enzymatic labels can include, but are not limited tohorseradish peroxidase (HRP), alkaline phosphatase (AP), glucoseoxidase, and β-galactosidase. The enzymatic label may be luciferase.

The methods, kits, and compositions disclosed herein may comprise afluorescent label. The fluorescent label may be an organic dye (e.g.,FITC), biological fluorophore (e.g., green fluorescent protein), orquantum dot. A non-limiting list of fluorescent labels includesfluorescein isothiocyante (FITC), DyLight Fluors, fluorescein, rhodamine(tetramethyl rhodamine isothiocyanate, TRITC), coumarin, Lucifer Yellow,and BODIPY. The label may be a fluorophore. Exemplary fluorophoresinclude, but are not limited to, indocarbocyanine (C3),indodicarbocyanine (C5), Cy3, Cy3.5, Cy5, Cy5.5, Cy7, Texas Red, PacificBlue, Oregon Green 488, Alexa Fluor®-355, Alexa Fluor 488, Alexa Fluor532, Alexa Fluor 546, Alexa Fluor-555, Alexa Fluor 568, Alexa Fluor 594,Alexa Fluor 647, Alexa Fluor 660, Alexa Fluor 680, JOE, Lissamine,Rhodamine Green, BODIPY, fluorescein isothiocyanate (FITC),carboxy-fluorescein (FAM), phycoerythrin, rhodamine, dichlororhodamine(dRhodamine), carboxy tetramethylrhodamine (TAMRA), carboxy-X-rhodamine(ROX™), LIZ™, VIC™, NED™, PET™, SYBR, PicoGreen, RiboGreen, and thelike. The fluorescent label may be a green fluorescent protein (GFP),red fluorescent protein (RFP), yellow fluorescent protein,phycobiliproteins (e.g., allophycocyanin, phycocyanin, phycoerythrin,and phycoerythrocyanin).

The methods disclosed herein may comprise one or more linkers. Themethods disclosed herein may comprise 1 or more, 2 or more, 3 or more, 4or more, 5 or more, 6 or more, 7 or more, 8 or more, 9 or more, 10 ormore, 20 or more, 30 or more, 40 or more, 50 or more, 60 or more, 70 ormore, 80 or more, 90 or more, 100 or more, 125 or more, 150 or more, 175or more, 200 or more, 250 or more, 300 or more, 350 or more, 400 ormore, 500 or more, 600 or more, 700 or more, 800 or more, 900 or more,or 1000 or more one or more linkers. The one or more linkers may bedifferent, similar, identical, or a combination thereof.

Suitable linkers comprise any chemical or biological compound capable ofattaching to a label, primer, and/or capture probe disclosed herein. Ifthe linker attaches to both the label and the primer or capture probe,then a suitable linker would be capable of sufficiently separating thelabel and the primer or capture probe. Suitable linkers would notsignificantly interfere with the ability of the primer and/or captureprobe to hybridize to a nucleic acid molecule, portion thereof, orvariant or derivative thereof. Suitable linkers would not significantlyinterfere with the ability of the label to be detected. The linker maybe rigid. The linker may be flexible. The linker may be semi rigid. Thelinker may be proteolytically stable (e.g., resistant to proteolyticcleavage). The linker may be proteolytically unstable (e.g., sensitiveto proteolytic cleavage). The linker may be helical. The linker may benon-helical. The linker may be coiled. The linker may be β-stranded. Thelinker may comprise a turn conformation. The linker may be a singlechain. The linker may be a long chain. The linker may be a short chain.The linker may comprise at least about 5 residues, at least about 10residues, at least about 15 residues, at least about 20 residues, atleast about 25 residues, at least about 30 residues, or at least about40 residues or more.

Examples of linkers include, but are not limited to, hydrazone,disulfide, thioether, and peptide linkers. The linker may be a peptidelinker. The peptide linker may comprise a proline residue. The peptidelinker may comprise an arginine, phenylalenine, threonine, glutamine,glutamate, or any combination thereof. The linker may be aheterobifunctional crosslinker.

The methods disclosed herein may comprise conducting 1 or more, 2 ormore, 3 or more, 4 or more, 5 or more, 6 or more, 7 or more, 8 or more,9 or more, 10 or more, 11 or more, 12 or more, 13 or more, 14 or more,15 or more, 20 or more, 25 or more, 30 or more, 35 or more, 40 or more,45 or more, or 50 or more assays on a sample comprising one or morenucleic acid molecules. The two or more assays may be different,similar, identical, or a combination thereof. For example, The methodsdisclosed herein comprise conducting two or more sequencing reactions.In another example, The methods disclosed herein comprise conducting twoor more assays, wherein at least one of the two or more assays comprisesa sequencing reaction. In yet another example, The methods disclosedherein comprise conducting two or more assays, wherein at least two ofthe two or more assays comprises a sequencing reaction and ahybridization reaction. The two or more assays may be performedsequentially, simultaneously, or a combination thereof. For example, thetwo or more sequencing reactions may be performed simultaneously. Inanother example, The methods disclosed herein comprise conducting ahybridization reaction, followed by a sequencing reaction. In yetanother example, The methods disclosed herein comprise conducting two ormore hybridization reactions simultaneously, followed by conducting twoor more sequencing reactions simultaneously. The two or more assays maybe performed by one or more devices. For example, two or moreamplification reactions may be performed by a PCR machine. In anotherexample, two or more sequencing reactions may be performed by two ormore sequencers.

Devices

The methods disclosed herein may comprise one or more devices. Themethods disclosed herein may comprise one or more assays comprising oneor more devices. The methods disclosed herein may comprise the use ofone or more devices to perform one or more steps or assays. The methodsdisclosed herein may comprise the use of one or more devices in one ormore steps or assays. For example, conducting a sequencing reaction maycomprise one or more sequencers. In another example, producing a subsetof nucleic acid molecules may comprise the use of one or more magneticseparators. In yet another example, one or more processors may be usedin the analysis of one or more nucleic acid samples. Exemplary devicesinclude, but are not limited to, sequencers, thermocyclers, real-timePCR instruments, magnetic separators, transmission devices,hybridization chambers, electrophoresis apparatus, centrifuges,microscopes, imagers, fluorometers, luminometers, plate readers,computers, processors, and bioanalyzers.

The methods disclosed herein may comprise one or more sequencers. Theone or more sequencers may comprise one or more HiSeq, MiSeq, HiScan,Genome Analyzer IIx, SOLiD Sequencer, Ion Torrent PGM, 454 GS Junior,Pac Bio RS, or a combination thereof. The one or more sequencers maycomprise one or more sequencing platforms. The one or more sequencingplatforms may comprise GS FLX by 454 Life Technologies/Roche, GenomeAnalyzer by Solexa/Illumina, SOLiD by Applied Biosystems, CGA Platformby Complete Genomics, PacBio RS by Pacific Biosciences, or a combinationthereof.

The methods disclosed herein may comprise one or more thermocyclers. Theone or more thermocyclers may be used to amplify one or more nucleicacid molecules. The methods disclosed herein may comprise one or morereal-time PCR instruments. The one or more real-time PCR instruments maycomprise a thermal cycler and a fluorimeter. The one or morethermocyclers may be used to amplify and detect one or more nucleic acidmolecules.

The methods disclosed herein may comprise one or more magneticseparators. The one or more magnetic separators may be used forseparation of paramagnetic and ferromagnetic particles from asuspension. The one or more magnetic separators may comprise one or moreLife Step™ biomagnetic separators, SPHERO™ FlexiMag separator, SPHERO™MicroMag separator, SPHERO™ HandiMag separator, SPHERO™ MiniTube Magseparator, SPHERO™ UltraMag separator, DynaMag™ magnet, DynaMag™-2Magnet, or a combination thereof.

The methods disclosed herein may comprise one or more bioanalyzers.Generally, a bioanalyzer is a chip-based capillary electrophoresismachine that can analyse RNA, DNA, and proteins. The one or morebioanalyzers may comprise Agilent's 2100 Bioanalyzer.

The methods disclosed herein may comprise one or more processors. Theone or more processors may analyze, compile, store, sort, combine,assess or otherwise process one or more data and/or results from one ormore assays, one or more data and/or results based on or derived fromone or more assays, one or more outputs from one or more assays, one ormore outputs based on or derived from one or more assays, one or moreoutputs from one or data and/or results, one or more outputs based on orderived from one or more data and/or results, or a combination thereof.The one or more processors may transmit the one or more data, results,or outputs from one or more assays, one or more data, results, oroutputs based on or derived from one or more assays, one or more outputsfrom one or more data or results, one or more outputs based on orderived from one or more data or results, or a combination thereof. Theone or more processors may receive and/or store requests from a user.The one or more processors may produce or generate one or more data,results, outputs. The one or more processors may produce or generate oneor more biomedical reports. The one or more processors may transmit oneor more biomedical reports. The one or more processors may analyze,compile, store, sort, combine, assess or otherwise process informationfrom one or more databases, one or more data or results, one or moreoutputs, or a combination thereof. The one or more processors mayanalyze, compile, store, sort, combine, assess or otherwise processinformation from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,17, 18, 19, 20, 30 or more databases. The one or more processors maytransmit one or more requests, data, results, outputs and/or informationto one or more users, processors, computers, computer systems, memorylocations, devices, databases, or a combination thereof. The one or moreprocessors may receive one or more requests, data, results, outputsand/or information from one or more users, processors, computers,computer systems, memory locations, devices, databases or a combinationthereof. The one or more processors may retrieve one or more requests,data, results, outputs and/or information from one or more users,processors, computers, computer systems, memory locations, devices,databases or a combination thereof.

The methods disclosed herein may comprise one or more memory locations.The one or more memory locations may store information, data, results,outputs, requests, or a combination thereof. The one or more memorylocations may receive information, data, results, outputs, requests, ora combination thereof from one or more users, processors, computers,computer systems, devices, or a combination thereof.

Methods described herein can be implemented with the aid of one or morecomputers and/or computer systems. A computer or computer system maycomprise electronic storage locations (e.g., databases, memory) withmachine-executable code for implementing the methods provided herein,and one or more processors for executing the machine-executable code.

Reference will now be made to the figures. It will be appreciated thatthe figures and features therein are not necessarily drawn to scale.

FIG. 1 shows a computer system (also “system” herein) 101 programmed orotherwise configured for implementing the methods of the disclosure,such as nucleic acid processing and/or analysis, and/or data analysis.The system 101 includes a central processing unit (CPU, also “processor”and “computer processor” herein) 105, which can be a single core ormulti core processor, or a plurality of processors for parallelprocessing. The system 101 also includes memory 110 (e.g., random-accessmemory, read-only memory, flash memory), electronic storage unit 115(e.g., hard disk), communications interface 120 (e.g., network adapter)for communicating with one or more other systems, and peripheral devices125, such as cache, other memory, data storage and/or electronic displayadapters. The memory 110, storage unit 115, interface 120 and peripheraldevices 125 are in communication with the CPU 105 through acommunications bus (solid lines), such as a motherboard. The storageunit 115 can be a data storage unit (or data repository) for storingdata. The system 101 is operatively coupled to a computer network(“network”) 130 with the aid of the communications interface 120. Thenetwork 130 can be the Internet, an internet and/or extranet, or anintranet and/or extranet that is in communication with the Internet. Thenetwork 130 in some cases is a telecommunication and/or data network.The network 130 can include one or more computer servers, which canenable distributed computing, such as cloud computing. The network 130in some cases, with the aid of the system 101, can implement apeer-to-peer network, which may enable devices coupled to the system 101to behave as a client or a server.

The system 101 is in communication with a processing system 135. Theprocessing system 135 can be configured to implement the methodsdisclosed herein. In some examples, the processing system 135 is anucleic acid sequencing system, such as, for example, a next generationsequencing system (e.g., Illumina sequencer, Ion Torrent sequencer,Pacific Biosciences sequencer). The processing system 135 can be incommunication with the system 101 through the network 130, or by direct(e.g., wired, wireless) connection. The processing system 135 can beconfigured for analysis, such as nucleic acid sequence analysis.

Methods as described herein can be implemented by way of machine (orcomputer processor) executable code (or software) stored on anelectronic storage location of the system 101, such as, for example, onthe memory 110 or electronic storage unit 115. During use, the code canbe executed by the processor 105. In some examples, the code can beretrieved from the storage unit 115 and stored on the memory 110 forready access by the processor 105. In some situations, the electronicstorage unit 115 can be precluded, and machine-executable instructionsare stored on memory 110.

The code can be pre-compiled and configured for use with a machine havea processer adapted to execute the code, or can be compiled duringruntime. The code can be supplied in a programming language that can beselected to enable the code to execute in a pre-compiled or as-compiledfashion.

Aspects of the systems and methods provided herein, such as the system1601, can be embodied in programming. Various aspects of the technologymay be thought of as “products” or “articles of manufacture” typicallyin the form of machine (or processor) executable code and/or associateddata that is carried on or embodied in a type of machine readablemedium. Machine-executable code can be stored on an electronic storageunit, such memory (e.g., read-only memory, random-access memory, flashmemory) or a hard disk. “Storage” type media can include any or all ofthe tangible memory of the computers, processors or the like, orassociated modules thereof, such as various semiconductor memories, tapedrives, disk drives and the like, which may provide non-transitorystorage at any time for the software programming. All or portions of thesoftware may at times be communicated through the Internet or variousother telecommunication networks. Such communications, for example, mayenable loading of the software from one computer or processor intoanother, for example, from a management server or host computer into thecomputer platform of an application server. Thus, another type of mediathat may bear the software elements includes optical, electrical andelectromagnetic waves, such as used across physical interfaces betweenlocal devices, through wired and optical landline networks and overvarious air-links. The physical elements that carry such waves, such aswired or wireless links, optical links or the like, also may beconsidered as media bearing the software. As used herein, unlessrestricted to non-transitory, tangible “storage” media, terms such ascomputer or machine “readable medium” refer to any medium thatparticipates in providing instructions to a processor for execution.

Hence, a machine readable medium, such as computer-executable code, maytake many forms, including but not limited to, a tangible storagemedium, a carrier wave medium or physical transmission medium.Non-volatile storage media include, for example, optical or magneticdisks, such as any of the storage devices in any computer(s) or thelike, such as may be used to implement the databases, etc. shown in thedrawings. Volatile storage media include dynamic memory, such as mainmemory of such a computer platform. Tangible transmission media includecoaxial cables; copper wire and fiber optics, including the wires thatcomprise a bus within a computer system. Carrier-wave transmission mediamay take the form of electric or electromagnetic signals, or acoustic orlight waves such as those generated during radio frequency (RF) andinfrared (IR) data communications. Common forms of computer-readablemedia therefore include for example: a floppy disk, a flexible disk,hard disk, magnetic tape, any other magnetic medium, a CD-ROM, DVD orDVD-ROM, any other optical medium, punch cards paper tape, any otherphysical storage medium with patterns of holes, a RAM, a ROM, a PROM andEPROM, a FLASH-EPROM, any other memory chip or cartridge, a carrier wavetransporting data or instructions, cables or links transporting such acarrier wave, or any other medium from which a computer may readprogramming code and/or data. Many of these forms of computer readablemedia may be involved in carrying one or more sequences of one or moreinstructions to a processor for execution.

The one or more computers and/or computer systems may analyze, compile,store, sort, combine, assess or otherwise process one or more dataand/or results from one or more assays, one or more data and/or resultsbased on or derived from one or more assays, one or more outputs fromone or more assays, one or more outputs based on or derived from one ormore assays, one or more outputs from one or data and/or results, one ormore outputs based on or derived from one or more data and/or results,or a combination thereof. The one or more computers and/or computersystems may transmit the one or more data, results, or outputs from oneor more assays, one or more data, results, or outputs based on orderived from one or more assays, one or more outputs from one or moredata or results, one or more outputs based on or derived from one ormore data or results, or a combination thereof. The one or morecomputers and/or computer systems may receive and/or store requests froma user. The one or more computers and/or computer systems may produce orgenerate one or more data, results, outputs. The one or more computersand/or computer systems may produce or generate one or more biomedicalreports. The one or more computers and/or computer systems may transmitone or more biomedical reports. The one or more computers and/orcomputer systems may analyze, compile, store, sort, combine, assess orotherwise process information from one or more databases, one or moredata or results, one or more outputs, or a combination thereof. The oneor more computers and/or computer systems may analyze, compile, store,sort, combine, assess or otherwise process information from 1, 2, 3, 4,5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 30 or moredatabases. The one or more computers and/or computer systems maytransmit one or more requests, data, results, outputs, and/orinformation to one or more users, processors, computers, computersystems, memory locations, devices, or a combination thereof. The one ormore computers and/or computer systems may receive one or more requests,data, results, outputs, and/or information from one or more users,processors, computers, computer systems, memory locations, devices, or acombination thereof. The one or more computers and/or computer systemsmay retrieve one or more requests, data, results, outputs and/orinformation from one or more users, processors, computers, computersystems, memory locations, devices, databases or a combination thereof.

The methods disclosed herein may comprise one or more transmissiondevices comprising an output means for transmitting one or more data,results, outputs, information, biomedical outputs, and/or biomedicalreports. The output means can take any form which transmits the data,results, requests, and/or information and may comprise a monitor,printed format, printer, computer, processor, memory location, or acombination thereof. The transmission device may comprise one or moreprocessors, computers, and/or computer systems for transmittinginformation.

Databases

The methods disclosed herein may comprise one or more databases. Themethods disclosed herein may comprise at least about 1, 2, 3, 4, 5, 6,7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 30 or moredatabases. The databases may comprise genomic, proteomic,pharmacogenomic, biomedical, and scientific databases. The databases maybe publicly available databases. Alternatively, or additionally, thedatabases may comprise proprietary databases. The databases may becommercially available databases. The databases include, but are notlimited to, MendelDB, PharmGKB, Varimed, Regulome, curated BreakSeqjunctions, Online Mendelian Inheritance in Man (OMIM), Human GenomeMutation Database (HGMD), NCBI dbSNP, NCBI RefSeq, GENCODE, GO (geneontology), and Kyoto Encyclopedia of Genes and Genomes (KEGG).

The methods disclosed herein may comprise analyzing one or moredatabases. The methods disclosed herein may comprise analyzing at leastabout 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19,20, 30 or more databases. Analyzing the one or more databases maycomprise one or more algorithms, computers, processors, memorylocations, devices, or a combination thereof.

The methods disclosed herein may comprise producing one or more probesbased on data and/or information from one or more databases. The methodsdisclosed herein may comprise producing one or more probe sets based ondata and/or information from one or more databases. The methodsdisclosed herein may comprise producing one or more probes and/or probesets based on data and/or information from at least about 2 or moredatabases. The methods disclosed herein may comprise producing one ormore probes and/or probe sets based on data and/or information from atleast about 3 or more databases. The methods disclosed herein maycomprise producing one or more probes and/or probe sets based on dataand/or information from at least about 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,14, 15, 16, 17, 18, 19, 20, 30 or more databases.

The methods disclosed herein may comprise identifying one or morenucleic acid regions based on data and/or information from one or moredatabases. The methods disclosed herein may comprise identifying one ormore sets of nucleic acid regions based on data and/or information fromone or more databases. The methods disclosed herein may compriseidentifying one or more nucleic acid regions and/or sets of nucleic acidregions based on data and/or information from at least about 2 or moredatabases. The methods disclosed herein may comprise identifying one ormore nucleic acid regions and/or sets of nucleic acid regions based ondata and/or information from at least about 3 or more databases. Themethods disclosed herein may comprise identifying one or more nucleicacid regions and/or sets of nucleic acid regions based on data and/orinformation from at least about 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,15, 16, 17, 18, 19, 20, 30 or more databases. The methods disclosedherein may further comprise producing one or more probes and/or probesets based on the identification of the one or more nucleic acid regionsand/or sets of nucleic acid regions.

The methods disclosed herein may comprise analyzing one or more resultsbased on data and/or information from one or more databases. The methodsdisclosed herein may comprise analyzing one or more sets of resultsbased on data and/or information from one or more databases. The methodsdisclosed herein may comprise analyzing one or more combined resultsbased on data and/or information from one or more databases. The methodsdisclosed herein may comprise analyzing one or more results, sets ofresults, and/or combined results based on data and/or information fromat least about 2 or more databases. The methods disclosed herein maycomprise analyzing one or more results, sets of results, and/or combinedresults based on data and/or information from at least about 3 or moredatabases. The methods disclosed herein may comprise analyzing one ormore results, sets of results, and/or combined results based on dataand/or information from at least about 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,14, 15, 16, 17, 18, 19, 20, 30 or more databases.

The methods disclosed herein may comprise comparing one or more resultsbased on data and/or information from one or more databases. The methodsdisclosed herein may comprise comparing one or more sets of resultsbased on data and/or information from one or more databases. The methodsdisclosed herein may comprise comparing one or more combined resultsbased on data and/or information from one or more databases. The methodsdisclosed herein may comprise comparing one or more results, sets ofresults, and/or combined results based on data and/or information fromat least about 2 or more databases. The methods disclosed herein maycomprise comparing one or more results, sets of results, and/or combinedresults based on data and/or information from at least about 3 or moredatabases. The methods disclosed herein may comprise comparing one ormore results, sets of results, and/or combined results based on dataand/or information from at least about 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,14, 15, 16, 17, 18, 19, 20, 30 or more databases.

The methods disclosed herein may comprise biomedical databases, genomicdatabases, biomedical reports, disease reports, case-control analysis,and rare variant discovery analysis based on data and/or informationfrom one or more databases, one or more assays, one or more data orresults, one or more outputs based on or derived from one or moreassays, one or more outputs based on or derived from one or more data orresults, or a combination thereof.

Analysis

The methods disclosed herein may comprise one or more data, one or moredata sets, one or more combined data, one or more combined data sets,one or more results, one or more sets of results, one or more combinedresults, or a combination thereof. The data and/or results may be basedon or derived from one or more assays, one or more databases, or acombination thereof. The methods disclosed herein may comprise analysisof the one or more data, one or more data sets, one or more combineddata, one or more combined data sets, one or more results, one or moresets of results, one or more combined results, or a combination thereof.The methods disclosed herein may comprise processing of the one or moredata, one or more data sets, one or more combined data, one or morecombined data sets, one or more results, one or more sets of results,one or more combined results, or a combination thereof.

The methods disclosed herein may comprise at least one analysis and atleast one processing of the one or more data, one or more data sets, oneor more combined data, one or more combined data sets, one or moreresults, one or more sets of results, one or more combined results, or acombination thereof. The methods disclosed herein may comprise one ormore analyses and one or more processing of the one or more data, one ormore data sets, one or more combined data, one or more combined datasets, one or more results, one or more sets of results, one or morecombined results, or a combination thereof. The methods disclosed hereinmay comprise at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 30, 40, 50,60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000 ormore distinct analyses of the one or more data, one or more data sets,one or more combined data, one or more combined data sets, one or moreresults, one or more sets of results, one or more combined results, or acombination thereof. The methods disclosed herein may comprise at least1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 100,200, 300, 400, 500, 600, 700, 800, 900, 1000 or more distinct processingof the one or more data, one or more data sets, one or more combineddata, one or more combined data sets, one or more results, one or moresets of results, one or more combined results, or a combination thereof.The one or more analyses and/or one or more processing may occursimultaneously, sequentially, or a combination thereof.

The one or more analyses and/or one or more processing may occur over 1,2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 20, 30, 40, 50, 60, 70, 80, 90,100, 200, 300, 400, 500, 600, 700, 800, 900, 1000 or time points. Thetime points may occur over a 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50, 55,60 or more hour period. The time points may occur over a 1, 2, 3, 4, 5,6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24,25, 30, 35, 40, 45, 50, 55, 60 or more day period. The time points mayoccur over a 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50, 55, 60 or more weekperiod. The time points may occur over a 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40,45, 50, 55, 60 or more month period. The time points may occur over a 1,2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,22, 23, 24, 25, 30, 35, 40, 45, 50, 55, 60 or more year period.

The methods disclosed herein may comprise one or more data. The one ormore data may comprise one or more raw data based on or derived from oneor more assays. The one or more data may comprise one or more raw databased on or derived from one or more databases. The one or more data maycomprise at least partially analyzed data based on or derived from oneor more raw data. The one or more data may comprise at least partiallyprocessed data based on or derived from one or more raw data. The one ormore data may comprise fully analyzed data based on or derived from oneor more raw data. The one or more data may comprise fully processed databased on or derived from one or more raw data. The data may comprisesequencing read data or expression data. The data may comprisebiomedical, scientific, pharmacological, and/or genetic information.

The methods disclosed herein may comprise one or more combined data. Theone or more combined data may comprise two or more data. The one or morecombined data may comprise two or more data sets. The one or morecombined data may comprise one or more raw data based on or derived fromone or more assays. The one or more combined data may comprise one ormore raw data based on or derived from one or more databases. The one ormore combined data may comprise at least partially analyzed data basedon or derived from one or more raw data. The one or more combined datamay comprise at least partially processed data based on or derived fromone or more raw data. The one or more combined data may comprise fullyanalyzed data based on or derived from one or more raw data. The one ormore combined data may comprise fully processed data based on or derivedfrom one or more raw data. One or more combined data may comprisesequencing read data or expression data. One or more combined data maycomprise biomedical, scientific, pharmacological, and/or geneticinformation.

The methods disclosed herein may comprise one or more data sets. The oneor more data sets may comprise one or more data. The one or more datasets may comprise one or more combined data. The one or more data setsmay comprise one or more raw data based on or derived from one or moreassays. The one or more data sets may comprise one or more raw databased on or derived from one or more databases. The one or more datasets may comprise at least partially analyzed data based on or derivedfrom one or more raw data. The one or more data sets may comprise atleast partially processed data based on or derived from one or more rawdata. The one or more data sets may comprise fully analyzed data basedon or derived from one or more raw data. The one or more data sets maycomprise fully processed data based on or derived from one or more rawdata. The data sets may comprise sequencing read data or expressiondata. The data sets may comprise biomedical, scientific,pharmacological, and/or genetic information.

The methods disclosed herein may comprise one or more combined datasets. The one or more combined data sets may comprise two or more data.The one or more combined data sets may comprise two or more combineddata. The one or more combined data sets may comprise two or more datasets. The one or more combined data sets may comprise one or more rawdata based on or derived from one or more assays. The one or morecombined data sets may comprise one or more raw data based on or derivedfrom one or more databases. The one or more combined data sets maycomprise at least partially analyzed data based on or derived from oneor more raw data. The one or more combined data sets may comprise atleast partially processed data based on or derived from one or more rawdata. The one or more combined data sets may comprise fully analyzeddata based on or derived from one or more raw data. The one or morecombined data sets may comprise fully processed data based on or derivedfrom one or more raw data. The methods disclosed herein may furthercomprise further processing and/or analysis of the combined data sets.One or more combined data sets may comprise sequencing read data orexpression data. One or more combined data sets may comprise biomedical,scientific, pharmacological, and/or genetic information.

The methods disclosed herein may comprise one or more results. The oneor more results may comprise one or more data, data sets, combined data,and/or combined data sets. The one or more results may be based on orderived from one or more data, data sets, combined data, and/or combineddata sets. The one or more results may be produced from one or moreassays. The one or more results may be based on or derived from one ormore assays. The one or more results may be based on or derived from oneor more databases. The one or more results may comprise at leastpartially analyzed results based on or derived from one or more data,data sets, combined data, and/or combined data sets. The one or moreresults may comprise at least partially processed results based on orderived from one or more data, data sets, combined data, and/or combineddata sets. The one or more results may comprise at fully analyzedresults based on or derived from one or more data, data sets, combineddata, and/or combined data sets. The one or more results may comprisefully processed results based on or derived from one or more data, datasets, combined data, and/or combined data sets. The results may comprisesequencing read data or expression data. The results may comprisebiomedical, scientific, pharmacological, and/or genetic information.

The methods disclosed herein may comprise one or more sets of results.The one or more sets of results may comprise one or more data, datasets, combined data, and/or combined data sets. The one or more sets ofresults may be based on or derived from one or more data, data sets,combined data, and/or combined data sets. The one or more sets ofresults may be produced from one or more assays. The one or more sets ofresults may be based on or derived from one or more assays. The one ormore sets of results may be based on or derived from one or moredatabases. The one or more sets of results may comprise at leastpartially analyzed sets of results based on or derived from one or moredata, data sets, combined data, and/or combined data sets. The one ormore sets of results may comprise at least partially processed sets ofresults based on or derived from one or more data, data sets, combineddata, and/or combined data sets. The one or more sets of results maycomprise at fully analyzed sets of results based on or derived from oneor more data, data sets, combined data, and/or combined data sets. Theone or more sets of results may comprise fully processed sets of resultsbased on or derived from one or more data, data sets, combined data,and/or combined data sets. The sets of results may comprise sequencingread data or expression data. The sets of results may comprisebiomedical, scientific, pharmacological, and/or genetic information.

The methods disclosed herein may comprise one or more combined results.The combined results may comprise one or more results, sets of results,and/or combined sets of results. The combined results may be based on orderived from one or more results, sets of results, and/or combined setsof results. The one or more combined results may comprise one or moredata, data sets, combined data, and/or combined data sets. The one ormore combined results may be based on or derived from one or more data,data sets, combined data, and/or combined data sets. The one or morecombined results may be produced from one or more assays. The one ormore combined results may be based on or derived from one or moreassays. The one or more combined results may be based on or derived fromone or more databases. The one or more combined results may comprise atleast partially analyzed combined results based on or derived from oneor more data, data sets, combined data, and/or combined data sets. Theone or more combined results may comprise at least partially processedcombined results based on or derived from one or more data, data sets,combined data, and/or combined data sets. The one or more combinedresults may comprise at fully analyzed combined results based on orderived from one or more data, data sets, combined data, and/or combineddata sets. The one or more combined results may comprise fully processedcombined results based on or derived from one or more data, data sets,combined data, and/or combined data sets. The combined results maycomprise sequencing read data or expression data. The combined resultsmay comprise biomedical, scientific, pharmacological, and/or geneticinformation.

The methods disclosed herein may comprise one or more combined sets ofresults. The combined sets of results may comprise one or more results,sets of results, and/or combined results. The combined sets of resultsmay be based on or derived from one or more results, sets of results,and/or combined results. The one or more combined sets of results maycomprise one or more data, data sets, combined data, and/or combineddata sets. The one or more combined sets of results may be based on orderived from one or more data, data sets, combined data, and/or combineddata sets. The one or more combined sets of results may be produced fromone or more assays. The one or more combined sets of results may bebased on or derived from one or more assays. The one or more combinedsets of results may be based on or derived from one or more databases.The one or more combined sets of results may comprise at least partiallyanalyzed combined sets of results based on or derived from one or moredata, data sets, combined data, and/or combined data sets. The one ormore combined sets of results may comprise at least partially processedcombined sets of results based on or derived from one or more data, datasets, combined data, and/or combined data sets. The one or more combinedsets of results may comprise at fully analyzed combined sets of resultsbased on or derived from one or more data, data sets, combined data,and/or combined data sets. The one or more combined sets of results maycomprise fully processed combined sets of results based on or derivedfrom one or more data, data sets, combined data, and/or combined datasets. The combined sets of results may comprise sequencing read data orexpression data. The combined sets of results may comprise biomedical,scientific, pharmacological, and/or genetic information.

The methods disclosed herein may comprise one or more outputs, sets ofoutputs, combined outputs, and/or combined sets of outputs. The methods,libraries, kits and systems herein may comprise producing one or moreoutputs, sets of outputs, combined outputs, and/or combined sets ofoutputs. The sets of outputs may comprise one or more outputs, one ormore combined outputs, or a combination thereof. The combined outputsmay comprise one or more outputs, one or more sets of outputs, one ormore combined sets of outputs, or a combination thereof. The combinedsets of outputs may comprise one or more outputs, one or more sets ofoutputs, one or more combined outputs, or a combination thereof. The oneor more outputs, sets of outputs, combined outputs, and/or combined setsof outputs may be based on or derived from one or more data, one or moredata sets, one or more combined data, one or more combined data sets,one or more results, one or more sets of results, one or more combinedresults, or a combination thereof. The one or more outputs, sets ofoutputs, combined outputs, and/or combined sets of outputs may be basedon or derived from one or more databases. The one or more outputs, setsof outputs, combined outputs, and/or combined sets of outputs maycomprise one or more biomedical reports, biomedical outputs, rarevariant outputs, pharmacogenetic outputs, population study outputs,case-control outputs, biomedical databases, genomic databases, diseasedatabases, net content.

The methods disclosed herein may comprise one or more biomedicaloutputs, one or more sets of biomedical outputs, one or more combinedbiomedical outputs, one or more combined sets of biomedical outputs. Themethods, libraries, kits and systems herein may comprise producing oneor more biomedical outputs, one or more sets of biomedical outputs, oneor more combined biomedical outputs, one or more combined sets ofbiomedical outputs. The sets of biomedical outputs may comprise one ormore biomedical outputs, one or more combined biomedical outputs, or acombination thereof. The combined biomedical outputs may comprise one ormore biomedical outputs, one or more sets of biomedical outputs, one ormore combined sets of biomedical outputs, or a combination thereof. Thecombined sets of biomedical outputs may comprise one or more biomedicaloutputs, one or more sets of biomedical outputs, one or more combinedbiomedical outputs, or a combination thereof. The one or more biomedicaloutputs, one or more sets of biomedical outputs, one or more combinedbiomedical outputs, one or more combined sets of biomedical outputs maybe based on or derived from one or more data, one or more data sets, oneor more combined data, one or more combined data sets, one or moreresults, one or more sets of results, one or more combined results, oneor more outputs, one or more sets of outputs, one or more combinedoutputs, one or more sets of combined outputs, or a combination thereof.The one or more biomedical outputs may comprise biomedical biomedicalinformation of a subject. The biomedical biomedical information of thesubject may predict, diagnose, and/or prognose one or more biomedicalfeatures. The one or more biomedical features may comprise the status ofa disease or condition, genetic risk of a disease or condition,reproductive risk, genetic risk to a fetus, risk of an adverse drugreaction, efficacy of a drug therapy, prediction of optimal drug dosage,transplant tolerance, or a combination thereof.

The methods disclosed herein may comprise one or more biomedicalreports. The methods, libraries, kits and systems herein may compriseproducing one or more biomedical reports. The one or more biomedicalreports may be based on or derived from one or more data, one or moredata sets, one or more combined data, one or more combined data sets,one or more results, one or more sets of results, one or more combinedresults, one or more outputs, one or more sets of outputs, one or morecombined outputs, one or more sets of combined outputs, one or morebiomedical outputs, one or more sets of biomedical outputs, combinedbiomedical outputs, one or more sets of biomedical outputs, or acombination thereof. The biomedical report may predict, diagnose, and/orprognose one or more biomedical features. The one or more biomedicalfeatures may comprise the status of a disease or condition, genetic riskof a disease or condition, reproductive risk, genetic risk to a fetus,risk of an adverse drug reaction, efficacy of a drug therapy, predictionof optimal drug dosage, transplant tolerance, or a combination thereof.

The methods disclosed herein may also comprise the transmission of oneor more data, information, results, outputs, reports or a combinationthereof. For example, data/information based on or derived from the oneor more assays are transmitted to another device and/or instrument. Inanother example, the data, results, outputs, biomedical outputs,biomedical reports, or a combination thereof are transmitted to anotherdevice and/or instrument. The information obtained from an algorithm mayalso be transmitted to another device and/or instrument. Informationbased on the analysis of one or more databases may be transmitted toanother device and/or instrument. Transmission of the data/informationmay comprise the transfer of data/information from a first source to asecond source. The first and second sources may be in the sameapproximate location (e.g., within the same room, building, block,campus). Alternatively, first and second sources may be in multiplelocations (e.g., multiple cities, states, countries, continents, etc).The data, results, outputs, biomedical outputs, biomedical reports canbe transmitted to a patient and/or a healthcare provider.

Transmission may be based on the analysis of one or more data, results,information, databases, outputs, reports, or a combination thereof. Forexample, transmission of a second report is based on the analysis of afirst report. Alternatively, transmission of a report is based on theanalysis of one or more data or results. Transmission may be based onreceiving one or more requests. For example, transmission of a reportmay be based on receiving a request from a user (e.g., patient,healthcare provider, individual).

Transmission of the data/information may comprise digital transmissionor analog transmission. Digital transmission may comprise the physicaltransfer of data (a digital bit stream) over a point-to-point orpoint-to-multipoint communication channel Examples of such channels arecopper wires, optical fibres, wireless communication channels, andstorage media. The data may be represented as an electromagnetic signal,such as an electrical voltage, radiowave, microwave, or infrared signal.

Analog transmission may comprise the transfer of a continuously varyinganalog signal. The messages can either be represented by a sequence ofpulses by means of a line code (baseband transmission), or by a limitedset of continuously varying wave forms (passband transmission), using adigital modulation method. The passband modulation and correspondingdemodulation (also known as detection) can be carried out by modemequipment. According to the most common definition of digital signal,both baseband and passband signals representing bit-streams areconsidered as digital transmission, while an alternative definition onlyconsiders the baseband signal as digital, and passband transmission ofdigital data as a form of digital-to-analog conversion.

The methods disclosed herein may comprise one or more sampleidentifiers. The sample identifiers may comprise labels, barcodes, andother indicators which can be linked to one or more samples and/orsubsets of nucleic acid molecules. The methods disclosed herein maycomprise one or more processors, one or more memory locations, one ormore computers, one or more monitors, one or more computer software, oneor more algorithms for linking data, results, outputs, biomedicaloutputs, and/or biomedical reports to a sample.

The methods disclosed herein may comprise a processor for correlatingthe expression levels of one or more nucleic acid molecules with aprognosis of disease outcome. The methods disclosed herein may compriseone or more of a variety of correlative techniques, including lookuptables, algorithms, multivariate models, and linear or nonlinearcombinations of expression models or algorithms. The expression levelsmay be converted to one or more likelihood scores, reflecting alikelihood that the patient providing the sample may exhibit aparticular disease outcome. The models and/or algorithms can be providedin machine readable format and can optionally further designate atreatment modality for a patient or class of patients.

Diseases or Conditions

The methods disclosed herein may comprise predicting, diagnosing, and/orprognosing a status or outcome of a disease or condition in a subjectbased on one or more biomedical outputs. Predicting, diagnosing, and/orprognosing a status or outcome of a disease in a subject may comprisediagnosing a disease or condition, identifying a disease or condition,determining the stage of a disease or condition, assessing the risk of adisease or condition, assessing the risk of disease recurrence,assessing reproductive risk, assessing genetic risk to a fetus,assessing the efficacy of a drug, assessing risk of an adverse drugreaction, predicting optimal drug dosage, predicting drug resistance, ora combination thereof.

The samples disclosed herein may be from a subject suffering from acancer. The sample may comprise malignant tissue, benign tissue, or amixture thereof. The cancer may be a recurrent and/or refractory cancer.Examples of cancers include, but are not limited to, sarcomas,carcinomas, lymphomas or leukemias.

Sarcomas are cancers of the bone, cartilage, fat, muscle, blood vessels,or other connective or supportive tissue. Sarcomas include, but are notlimited to, bone cancer, fibrosarcoma, chondrosarcoma, Ewing's sarcoma,malignant hemangioendothelioma, malignant schwannoma, bilateralvestibular schwannoma, osteosarcoma, soft tissue sarcomas (e.g. alveolarsoft part sarcoma, angiosarcoma, cystosarcoma phylloides,dermatofibrosarcoma, desmoid tumor, epithelioid sarcoma, extraskeletalosteosarcoma, fibrosarcoma, hemangiopericytoma, hemangiosarcoma,Kaposi's sarcoma, leiomyosarcoma, liposarcoma, lymphangiosarcoma,lymphosarcoma, malignant fibrous histiocytoma, neurofibrosarcoma,rhabdomyosarcoma, and synovial sarcoma).

Carcinomas are cancers that begin in the epithelial cells, which arecells that cover the surface of the body, produce hormones, and make upglands. By way of non-limiting example, carcinomas include breastcancer, pancreatic cancer, lung cancer, colon cancer, colorectal cancer,rectal cancer, kidney cancer, bladder cancer, stomach cancer, prostatecancer, liver cancer, ovarian cancer, brain cancer, vaginal cancer,vulvar cancer, uterine cancer, oral cancer, penile cancer, testicularcancer, esophageal cancer, skin cancer, cancer of the fallopian tubes,head and neck cancer, gastrointestinal stromal cancer, adenocarcinoma,cutaneous or intraocular melanoma, cancer of the anal region, cancer ofthe small intestine, cancer of the endocrine system, cancer of thethyroid gland, cancer of the parathyroid gland, cancer of the adrenalgland, cancer of the urethra, cancer of the renal pelvis, cancer of theureter, cancer of the endometrium, cancer of the cervix, cancer of thepituitary gland, neoplasms of the central nervous system (CNS), primaryCNS lymphoma, brain stem glioma, and spinal axis tumors. The cancer maybe a skin cancer, such as a basal cell carcinoma, squamous, melanoma,nonmelanoma, or actinic (solar) keratosis.

The cancer may be a lung cancer. Lung cancer can start in the airwaysthat branch off the trachea to supply the lungs (bronchi) or the smallair sacs of the lung (the alveoli). Lung cancers include non-small celllung carcinoma (NSCLC), small cell lung carcinoma, and mesotheliomia.Examples of NSCLC include squamous cell carcinoma, adenocarcinoma, andlarge cell carcinoma. The mesothelioma may be a cancerous tumor of thelining of the lung and chest cavity (pleura) or lining of the abdomen(peritoneum). The mesothelioma may be due to asbestos exposure. Thecancer may be a brain cancer, such as a glioblastoma.

Alternatively, the cancer may be a central nervous system (CNS) tumor.CNS tumors may be classified as gliomas or nongliomas. The glioma may bemalignant glioma, high grade glioma, diffuse intrinsic pontine glioma.Examples of gliomas include astrocytomas, oligodendrogliomas (ormixtures of oligodendroglioma and astocytoma elements), and ependymomas.Astrocytomas include, but are not limited to, low-grade astrocytomas,anaplastic astrocytomas, glioblastoma multiforme, pilocytic astrocytoma,pleomorphic xanthoastrocytoma, and subependymal giant cell astrocytoma.Oligodendrogliomas include low-grade oligodendrogliomas (oroligoastrocytomas) and anaplastic oligodendriogliomas. Nongliomasinclude meningiomas, pituitary adenomas, primary CNS lymphomas, andmedulloblastomas. The cancer may be a meningioma.

The leukemia may be an acute lymphocytic leukemia, acute myelocyticleukemia, chronic lymphocytic leukemia, or chronic myelocytic leukemia.Additional types of leukemias include hairy cell leukemia, chronicmyelomonocytic leukemia, and juvenile myelomonocytic leukemia.

Lymphomas are cancers of the lymphocytes and may develop from either Bor T lymphocytes. The two major types of lymphoma are Hodgkin'slymphoma, previously known as Hodgkin's disease, and non-Hodgkin'slymphoma. Hodgkin's lymphoma is marked by the presence of theReed-Sternberg cell. Non-Hodgkin's lymphomas are all lymphomas which arenot Hodgkin's lymphoma. Non-Hodgkin lymphomas may be indolent lymphomasand aggressive lymphomas. Non-Hodgkin's lymphomas include, but are notlimited to, diffuse large B cell lymphoma, follicular lymphoma,mucosa-associated lymphatic tissue lymphoma (MALT), small celllymphocytic lymphoma, mantle cell lymphoma, Burkitt's lymphoma,mediastinal large B cell lymphoma, Waldenstrom macroglobulinemia, nodalmarginal zone B cell lymphoma (NMZL), splenic marginal zone lymphoma(SMZL), extranodal marginal zone B cell lymphoma, intravascular large Bcell lymphoma, primary effusion lymphoma, and lymphomatoidgranulomatosis.

Additional diseases and/or conditions include, but are not limited to,atherosclerosis, inflammatory diseases, autoimmune diseases, rheumaticheart disease. Examples of inflammatory diseases include, but are notlimited to, acne vulgaris, Alzheimer's, ankylosing spondylitis,arthritis (osteoarthritis, rheumatoid arthritis (RA), psoriaticarthritis), asthma, atherosclerosis, celiac disease, chronicprostatitis, Crohn's disease, colitis, dermatitis, diverticulitis,fibromyalgia, glomerulonephritis hepatitis, irritable bowel syndrome(IBS), systemic lupus erythematous (SLE), nephritis, Parkinson'sdisease, pelvic inflammatory disease, sarcoidosis, ulcerative colitis,and vasculitis.

Examples of autoimmune diseases include, but are not limited to, acutedisseminated encephalomyelitis (ADEM), Addison's disease,agammaglobulinemia, alopecia areata, amyotrophic Lateral Sclerosis,ankylosing spondylitis, antiphospholipid syndrome, antisynthetasesyndrome, atopic allergy, atopic dermatitis, autoimmune aplastic anemia,autoimmune cardiomyopathy, autoimmune enteropathy, autoimmune hemolyticanemia, autoimmune hepatitis, autoimmune inner ear disease, autoimmunelymphoproliferative syndrome, autoimmune peripheral neuropathy,autoimmune pancreatitis, autoimmune polyendocrine syndrome, autoimmuneprogesterone dermatitis, autoimmune thrombocytopenic purpura, autoimmuneurticaria, autoimmune uveitis, Balo disease/Balo concentric sclerosis,Behçet's disease, Berger's disease, Bickerstaff s encephalitis, Blausyndrome, bullous pemphigoid, Castleman's disease, celiac disease,Chagas disease, chronic inflammatory demyelinating polyneuropathy,chronic recurrent multifocal osteomyelitis, chronic obstructivepulmonary disease, Churg-Strauss syndrome, cicatricial pemphigoid, Cogansyndrome, cold agglutinin disease, complement component 2 deficiency,contact dermatitis, cranial arteritis, CREST syndrome, Crohn's disease,Cushing's syndrome, cutaneous leukocytoclastic angiitis, Dego'sdiseasevDercum's disease, dermatitis herpetiformis, dermatomyositis,diabetes mellitus type 1, diffuse cutaneous systemic sclerosis,Dressler's syndrome, drug-induced lupus, discoid lupus erythematosus,eczema, endometriosis, enthesitis-related arthritis, eosinophilicfasciitis, eosinophilic gastroenteritisvepidermolysis bullosa acquisita,erythema nodosum, erythroblastosis fetalis, essential mixedcryoglobulinemia, Evan's syndrome, fibrodysplasia ossificansprogressiva, fibrosing alveolitis (or idiopathic pulmonary fibrosis),gastritis, gastrointestinal pemphigoid, giant cell arteritis,glomerulonephritis, Goodpasture's syndrome, Graves' disease,Guillain-Barré syndrome (GBS), Hashimoto's encephalopathy, Hashimoto'sthyroiditisvHenoch-Schonlein purpuravherpes gestationis aka gestationalpemphigoid, hidradenitis suppurativa, Hughes-Stovin syndrome,hypogammaglobulinemia, idiopathic inflammatory demyelinating diseases,idiopathic pulmonary fibrosis, IgA nephropathy, inclusion body myositis,chronic inflammatory demyelinating polyneuropathyvinterstitial cystitis,juvenile idiopathic arthritis aka juvenile rheumatoid arthritis,Kawasaki's disease, Lambert-Eaton myasthenic syndrome, leukocytoclasticvasculitis, Lichen planus, Lichen sclerosus, linear IgA disease (LAD),Lou Gehrig's disease (Also Amyotrophic lateral sclerosis), lupoidhepatitis aka autoimmune hepatitis, lupus erythematosus, Majeedsyndrome, Meniere's disease, microscopic polyangiitis, mixed connectivetissue disease, morphea, Mucha-Habermann disease, multiple sclerosis,myasthenia gravis, myositis, neuromyelitis optica (also Devic'sdisease), neuromyotonia, occular cicatricial pemphigoid, opsoclonusmyoclonus syndrome, Ord's thyroiditis, palindromic rheumatism, PANDAS(pediatric autoimmune neuropsychiatric disorders associated withstreptococcus), paraneoplastic cerebellar degeneration, paroxysmalnocturnal hemoglobinuria (PNH), Parry Romberg syndrome, Parsonage-Turnersyndrome, Pars planitis, pemphigus vulgaris, pernicious anaemia,perivenous encephalomyelitis, POEMS syndrome, polyarteritis nodosa,polymyalgia rheumatica, polymyositis, primary biliary cirrhosis, primarysclerosing cholangitis, progressive inflammatory neuropathy, psoriasis,psoriatic arthritis, pyoderma gangrenosum, pure red cell aplasia,Rasmussen's encephalitis, Raynaud phenomenon, relapsing polychondritis,Reiter's syndrome, restless leg syndrome, retroperitoneal fibrosis,rheumatoid arthritis, rheumatic fever, sarcoidosis, Schmidt syndromeanother form of APS, Schnitzler syndrome, scleritis, scleroderma, serumsickness, Sjögren's syndrome, spondyloarthropathy, Stiff personsyndrome, subacute bacterial endocarditis (SBE), Susac's syndrome,Sweet's syndrome, sympathetic ophthalmia, Takayasu's arteritis, temporalarteritis (also known as “giant cell arteritis”), thrombocytopenia,Tolosa-Hunt syndrome, transverse myelitis, ulcerative colitis,undifferentiated connective tissue disease different from mixedconnective tissue disease, undifferentiated spondyloarthropathy,urticarial vasculitis, vasculitis, vitiligo, and Wegener'sgranulomatosis.

The methods provided herein may also be useful for detecting,monitoring, diagnosing and/or predicting a subject's response to animplanted device. Exemplary medical devices include but are not limitedto stents, replacement heart valves, implanted cerebella stimulators,hip replacement joints, breast implants, and knee implants.

The methods disclosed herein may be used for monitoring the health of afetus using whole or partial genome analysis of nucleic acids derivedfrom a fetus, as compared to the maternal genome. For example, nucleicacids can be useful in pregnant subjects for fetal diagnostics, withfetal nucleic acids serving as a marker for gender, rhesus D status,fetal aneuploidy, and sex-linked disorders. The methods disclosed hereinmay identify fetal mutations or genetic abnormalities. The methodsdisclosed herein can enable detection of extra or missing chromosomes,particularly those typically associated with birth defects ormiscarriage. The methods disclosed herein may comprise the diagnosis,prediction or monitoring of autosomal trisomies (e.g., Trisomy 13, 15,16, 18, 21, or 22) may be based on the detection of foreign molecules.The trisomy may be associated with an increased chance of miscarriage(e.g., Trisomy 15, 16, or 22). Alternatively, the trisomy that isdetected is a liveborn trisomy that may indicate that an infant will beborn with birth defects (e.g., Trisomy 13 (Patau Syndrome), Trisomy 18(Edwards Syndrome), and Trisomy 21 (Down Syndrome)). The abnormality mayalso be of a sex chromosome (e.g., XXY (Klinefelter's Syndrome), XYY(Jacobs Syndrome), or XXX (Trisomy X). The methods disclosed herein maycomprise one or more genomic regions on the following chromosomes: 13,18, 21, X, or Y. For example, the foreign molecule may be on chromosome21 and/or on chromosome 18, and/or on chromosome 13. The one or moregenomic regions may comprise multiple sites on multiple chromosomes.

Further fetal conditions that can be determined based on the methods andsystems herein include monosomy of one or more chromosomes (X chromosomemonosomy, also known as Turner's syndrome), trisomy of one or morechromosomes (13, 18, 21, and X), tetrasomy and pentasomy of one or morechromosomes (which in humans is most commonly observed in the sexchromosomes, e.g. XXXX, XXYY, XXXY, XYYY, XXXXX, XXXXY, XXXYY, XYYYY andXXYYY), monoploidy, triploidy (three of every chromosome, e.g. 69chromosomes in humans), tetraploidy (four of every chromosome, e.g. 92chromosomes in humans), pentaploidy and multiploidy.

The methods disclosed may comprise detecting, monitoring, quantitating,or evaluating one or more pathogen-derived nucleic acid molecules or oneor more diseases or conditions caused by one or more pathogens.Exemplary pathogens include, but are not limited to, Bordetella,Borrelia, Brucella, Campylobacter, Chlamydia, Chlamydophila,Clostridium, Corynebacterium, Enterococcus, Escherichia, Francisella,Haemophilus, Helicobacter, Legionella, Leptospira, Listeria,Mycobacterium, Mycoplasma, Neisseria, Pseudomonas, Rickettsia,Salmonella, Shigella, Staphylococcus, Streptococcus, Treponema, Vibrio,or Yersinia. Additional pathogens include, but are not limited to,Mycobacterium tuberculosis, Streptococcus, Pseudomonas, Shigella,Campylobacter, and Salmonella.

The disease or conditions caused by one or more pathogens may comprisetuberculosis, pneumonia, foodborne illnesses, tetanus, typhoid fever,diphtheria, syphilis, leprosy, bacterial vaginosis, bacterialmeningitis, bacterial pneumonia, a urinary tract infection, bacterialgastroenteritis, and bacterial skin infection. Examples of bacterialskin infections include, but are not limited to, impetigo which may becaused by Staphylococcus aureus or Streptococcus pyogenes; erysipelaswhich may be caused by a streptococcus bacterial infection of the deepepidermis with lymphatic spread; and cellulitis which may be caused bynormal skin flora or by exogenous bacteria.

The pathogen may be a fungus, such as, Candida, Aspergillus,Cryptococcus, Histoplasma, Pneumocystis, and Stachybotrys. Examples ofdiseases or conditions caused by a fungus include, but are not limitedto, jock itch, yeast infection, ringworm, and athlete's foot.

The pathogen may be a virus. Examples of viruses include, but are notlimited to, adenovirus, coxsackievirus, Epstein-Barr virus, Hepatitisvirus (e.g., Hepatitis A, B, and C), herpes simplex virus (type 1 and2), cytomegalovirus, herpes virus, HIV, influenza virus, measles virus,mumps virus, papillomavirus, parainfluenza virus, poliovirus,respiratory syncytial virus, rubella virus, and varicella-zoster virus.Examples of diseases or conditions caused by viruses include, but arenot limited to, cold, flu, hepatitis, AIDS, chicken pox, rubella, mumps,measles, warts, and poliomyelitis.

The pathogen may be a protozoan, such as Acanthamoeba (e.g., A.astronyxis, A. castellanii, A. culbertsoni, A. hatchetti, A. polyphaga,A. rhysodes, A. healyi, A. divionensis), Brachiola (e.g., B connori, B.vesicularum), Cryptosporidium (e.g., C. parvum), Cyclospora (e.g., C.cayetanensis), Encephalitozoon (e.g., E. cuniculi, E. hellem, E.intestinalis), Entamoeba (e.g., E. histolytica), Enterocytozoon (e.g.,E. bieneusi), Giardia (e.g., G. lamblia), Isospora (e.g, I. belli),Microsporidium (e.g., M. africanum, M. ceylonensis), Naegleria (e.g., N.fowleri), Nosema (e.g., N. algerae, N. ocularum), Pleistophora,Trachipleistophora (e.g., T. anthropophthera, T. hominis), andVittaforma (e.g., V. corneae).

Therapeutics

The methods disclosed herein may comprise treating and/or preventing adisease or condition in a subject based on one or more biomedicaloutputs. The one or more biomedical outputs may recommend one or moretherapies. The one or more biomedical outputs may suggest, select,designate, recommend or otherwise determine a course of treatment and/orprevention of a disease or condition. The one or more biomedical outputsmay recommend modifying or continuing one or more therapies. Modifyingone or more therapies may comprise administering, initiating, reducing,increasing, and/or terminating one or more therapies. The one or moretherapies comprise an anti-cancer, antiviral, antibacterial, antifungal,immunosuppressive therapy, or a combination thereof. The one or moretherapies may treat, alleviate, or prevent one or more diseases orindications.

Examples of anti-cancer therapies include, but are not limited to,surgery, chemotherapy, radiation therapy, immunotherapy/biologicaltherapy, photodynamic therapy. Anti-cancer therapies may comprisechemotherapeutics, monoclonal antibodies (e.g., rituximab, trastuzumab),cancer vaccines (e.g., therapeutic vaccines, prophylactic vaccines),gene therapy, or combination thereof.

The one or more therapies may comprise an antimicrobial. Generally, anantimicrobial refers to a substance that kills or inhibits the growth ofmicroorganisms such as bacteria, fungi, virus, or protozoans.Antimicrobial drugs either kill microbes (microbicidal) or prevent thegrowth of microbes (microbiostatic). There are mainly two classes ofantimicrobial drugs, those obtained from natural sources (e.g.,antibiotics, protein synthesis inhibitors (such as aminoglycosides,macrolides, tetracyclines, chloramphenicol, polypeptides)) and syntheticagents (e.g., sulphonamides, cotrimoxazole, quinolones). In someinstances, the antimicrobial drug is an antibiotic, anti-viral,anti-fungal, anti-malarial, anti-tuberculosis drug, anti-leprotic, oranti-protozoal.

Antibiotics are generally used to treat bacterial infections.Antibiotics may be divided into two categories: bactericidal antibioticsand bacteriostatic antibiotics. Generally, bactericidals may killbacteria directly where bacteriostatics may prevent them from dividing.Antibiotics may be derived from living organisms or may includesynthetic antimicrobials, such as the sulfonamides. Antibiotics mayinclude aminoglycosides, such as amikacin, gentamicin, kanamycin,neomycin, netilmicin, tobramycin, and paromomycin. Alternatively,antibiotics may be ansamycins (e.g., geldanamycin, herbimycin),cabacephems (e.g., loracarbef), carbapenems (e.g., ertapenem, doripenem,imipenem, cilastatin, meropenem), glycopeptides (e.g., teicoplanin,vancomycin, telavancin), lincosamides (e.g., clindamycin, lincomycin,daptomycin), macrolides (e.g., azithromycin, clarithromycin,dirithromycin, erythromycin, roxithromycin, troleandomycin,telithromycin, spectinomycin, spiramycin), nitrofurans (e.g.,furazolidone, nitrofurantoin), and polypeptides (e.g., bacitracin,colistin, polymyxin B).

In some instances, the antibiotic therapy includes cephalosporins suchas cefadroxil, cefazolin, cefalotin, cefalexin, cefaclor, cefamandole,cefoxitin, cefprozil, cefuroxime, cefixime, cefdinir, cefditoren,cefoperazone, cefotaxime, cefpodoxime, ceftazidime, ceftibuten,ceftizoxime, ceftriaxone, cefepime, ceftaroline fosamil, andceftobiprole.

The antibiotic therapy may also include penicillins. Examples ofpenicillins include amoxicillin, ampicillin, azlocillin, carbenicillin,cloxacillin, dicloxacillin, flucloxacillin, mezlocillin, methicillin,nafcillin, oxacillin, penicillin g, penicillin v, piperacillin,temocillin, and ticarcillin.

Alternatively, quinolines may be used to treat a bacterial infection.Examples of quinilones include ciprofloxacin, enoxacin, gatifloxacin,levofloxacin, lomefloxacin, moxifloxacin, nalidixic acid, norfloxacin,ofloxacin, trovafloxacin, grepafloxacin, sparfloxacin, and temafloxacin.

In some instances, the antibiotic therapy comprises a combination of twoor more therapies. For example, amoxicillin and clavulanate, ampicillinand sulbactam, piperacillin and tazobactam, or ticarcillin andclavulanate may be used to treat a bacterial infection.

Sulfonamides may also be used to treat bacterial infections. Examples ofsulfonamides include, but are not limited to, mafenide,sulfonamidochrysoidine, sulfacetamide, sulfadiazine, silversulfadiazine, sulfamethizole, sulfamethoxazole, sulfanilimide,sulfasalazine, sulfisoxazole, trimethoprim, andtrimethoprim-sulfamethoxazole (co-trimoxazole) (tmp-smx).

Tetracyclines are another example of antibiotics. Tetracyclines mayinhibit the binding of aminoacyl-tRNA to the mRNA-ribosome complex bybinding to the 30S ribosomal subunit in the mRNA translation complex.Tetracyclines include demeclocycline, doxycycline, minocycline,oxytetracycline, and tetracycline. Additional antibiotics that may beused to treat bacterial infections include arsphenamine,chloramphenicol, fosfomycin, fusidic acid, linezolid, metronidazole,mupirocin, platensimycin, quinupristin/dalfopristin, rifaximin,thiamphenicol, tigecycline, tinidazole, clofazimine, dapsone,capreomycin, cycloserine, ethambutol, ethionamide, isoniazid,pyrazinamide, rifampicin, rifamycin, rifabutin, rifapentine, andstreptomycin.

Antiviral therapies are a class of medication used specifically fortreating viral infections. Like antibiotics, specific antivirals areused for specific viruses. They are relatively harmless to the host, andtherefore can be used to treat infections. Antiviral therapies mayinhibit various stages of the viral life cycle. For example, anantiviral therapy may inhibit attachment of the virus to a cellularreceptor. Such antiviral therapies may include agents that mimic thevirus associated protein (VAP and bind to the cellular receptors. Otherantiviral therapies may inhibit viral entry, viral uncoating (e.g.,amantadine, rimantadine, pleconaril), viral synthesis, viralintegration, viral transcription, or viral translation (e.g.,fomivirsen). In some instances, the antiviral therapy is a morpholinoantisense. Antiviral therapies should be distinguished from viricides,which actively deactivate virus particles outside the body.

Many of the antiviral drugs available are designed to treat infectionsby retroviruses, mostly HIV. Antiretroviral drugs may include the classof protease inhibitors, reverse transcriptase inhibitors, and integraseinhibitors. Drugs to treat HIV may include a protease inhibitor (e.g.,invirase, saquinavir, kaletra, lopinavir, lexiva, fosamprenavir, norvir,ritonavir, prezista, duranavir, reyataz, viracept), integrase inhibitor(e.g., raltegravir), transcriptase inhibitor (e.g., abacavir, ziagen,agenerase, amprenavir, aptivus, tipranavir, crixivan, indinavir,fortovase, saquinavir, Intelence™, etravirine, isentress, viread),reverse transcriptase inhibitor (e.g., delavirdine, efavirenz, epivir,hivid, nevirapine, retrovir, AZT, stuvadine, truvada, videx), fusioninhibitor (e.g., fuzeon, enfuvirtide), chemokine coreceptor antagonist(e.g., selzentry, emtriva, emtricitabine, epzicom, or trizivir).Alternatively, antiretroviral therarapies may be combination therapies,such as atripla (e.g., efavirenz, emtricitabine, and tenofoviradisoproxil fumarate) and completer (embricitabine, rilpivirine, andtenofovir disoproxil fumarate). Herpes viruses, best known for causingcold sores and genital herpes, are usually treated with the nucleosideanalogue acyclovir. Viral hepatitis (A-E) are caused by five unrelatedhepatotropic viruses and are also commonly treated with antiviral drugsdepending on the type of infection. Influenza A and B viruses areimportant targets for the development of new influenza treatments toovercome the resistance to existing neuraminidase inhibitors such asoseltamivir.

In some instances, the antiviral therapy may comprise a reversetranscriptase inhibitor. Reverse transcriptase inhibitors may benucleoside reverse transcriptase inhibitors or non-nucleoside reversetranscriptase inhibitors. Nucleoside reverse transcriptase inhibitorsmay include, but are not limited to, combivir, emtriva, epivir, epzicom,hivid, retrovir, trizivir, truvada, videx ec, videx, viread, zerit, andziagen. Non-nucleoside reverse transcriptase inhibitors may compriseedurant, intelence, rescriptor, sustiva, and viramune (immediate releaseor extended release).

Protease inhibitors are another example of antiviral drugs and mayinclude, but are not limited to, agenerase, aptivus, crixivan,fortovase, invirase, kaletra, lexiva, norvir, prezista, reyataz, andviracept. Alternatively, the antiviral therapy may comprise a fusioninhibitor (e.g., enfuviride) or an entry inhibitor (e.g., maraviroc).

Additional examples of antiviral drugs include abacavir, acyclovir,adefovir, amantadine, amprenavir, ampligen, arbidol, atazanavir,atripla, boceprevir, cidofovir, combivir, darunavir, delavirdine,didanosine, docosanol, edoxudine, efavirenz, emtricitabine, enfuvirtide,entecavir, famciclovir, fomivirsen, fosamprenavir, foscarnet, fosfonet,fusion inhibitors, ganciclovir, ibacitabine, imunovir, idoxuridine,imiquimod, indinavir, inosine, integrase inhibitor, interferons (e.g.,interferon type I, II, III), lamivudine, lopinavir, loviride, maraviroc,moroxydine, methisazone, nelfinavir, nevirapine, nexavir, nucleosideanalogues, oseltamivir, peg-interferon alfa-2a, penciclovir, peramivir,pleconaril, podophyllotoxin, protease inhibitors, raltegravir, reversetranscriptase inhibitors, ribavirin, rimantadine, ritonavir, pyramidine,saquinavir, stavudine, tea tree oil, tenofovir, tenofovir disoproxil,tipranavir, trifluridine, trizivir, tromantadine, truvada, valaciclovir,valganciclovir, vicriviroc, vidarabine, viramidine, zalcitabine,zanamivir, and zidovudine.

An antifungal drug is medication that may be used to treat fungalinfections such as athlete's foot, ringworm, candidiasis (thrush),serious systemic infections such as cryptococcal meningitis, and others.Antifungals work by exploiting differences between mammalian and fungalcells to kill off the fungal organism. Unlike bacteria, both fungi andhumans are eukaryotes. Thus, fungal and human cells are similar at themolecular level, making it more difficult to find a target for anantifungal drug to attack that does not also exist in the infectedorganism.

Antiparasitics are a class of medications which are indicated for thetreatment of infection by parasites, such as nematodes, cestodes,trematodes, infectious protozoa, and amoebae. Like antifungals, theymust kill the infecting pest without serious damage to the host.

Systems, Kits, and Libraries

Methods of the disclosure can be implemented by way of systems, kits,libraries, or a combination thereof. The methods of the invention maycomprise one or more systems. Systems of the disclosure can beimplemented by way of kits, libraries, or both. A system may compriseone or more components to perform any of the methods or any of the stepsof the methods disclosed herein. For example, a system may comprise oneor more kits, devices, libraries, or a combination thereof. A system maycomprise one or more sequencers, processors, memory locations,computers, computer systems, or a combination thereof. A system maycomprise a transmission device.

A kit may comprise various reagents for implementing various operationsdisclosed herein, including sample processing and/or analysisoperations. A kit may comprise instructions for implementing at leastsome of the operations disclosed herein. A kit may comprise one or morecapture probes, one or more beads, one or more labels, one or morelinkers, one or more devices, one or more reagents, one or more buffers,one or more samples, one or more databases, or a combination thereof.

A library may comprise one or more capture probes. A library maycomprise one or more subsets of nucleic acid molecules. A library maycomprise one or more databases. A library may be produced or generatedfrom any of the methods, kits, or systems disclosed herein. A databaselibrary may be produced from one or more databases. A method forproducing one or more libraries may comprise (a) aggregating informationfrom one or more databases to produce an aggregated data set; (b)analyzing the aggregated data set; and (c) producing one or moredatabase libraries from the aggregated data set.

EXAMPLES

Methods and systems of the present disclosure may be applied to varioustypes of samples, such as nucleic acid samples, protein samples, orother biological samples.

While preferred embodiments of the present invention have been shown anddescribed herein, it will be obvious to those skilled in the art thatsuch embodiments are provided by way of example only. Numerousvariations, changes, and substitutions will now occur to those skilledin the art without departing from the invention. It should be understoodthat various alternatives to the embodiments of the invention describedherein may be employed in practicing the invention. It is intended thatthe following claims define the scope of the invention and that methodsand structures within the scope of these claims and their equivalents becovered thereby.

Example 1. Three Independent Workflows for the Production of ESP, HGCPand LRP Libraries

This example provides three independent workflows for the preparation ofan Exome Supplement Plus (ESP), high GC content (HGCP) and specificenrichment pulldown (LRP) library from a single nucleic acid sample.

Illumina's RSB (or 50 mM Sodium Ascorbic) was added to three differentCovaris microtubes containing 1 μg of genomic DNA (DNA) from a singlesample to produce 52.5 μL of total volume in each microtube. Themicrotubes were designated as ESP, HGCP, and LRP. The gDNA in themicrotube was sheared using the Covaris settings in Table 1.

TABLE 1 Covaris settings ESP HGCP LRP Duty factor:    20%    20%    20%Cyc/burst: 200  200  200  Time (sec): 80 80 25 Peak Incident Power (W):50 50 50 Temp (*C): 20 20 20

The microtubes were spun down and 50 μL of the fragmented DNA weretransferred to PCR plates. 10 μL of RSB was added to each well. The HGCPsample plate was heated at 65° C. for 5 minutes. The ESP and LRP plateswere not heated at 65° C. 40 μL Illumina's ERP was added to each sampleplate by pipetting up and down to mix. The plates were sealed. Theplates were incubated at 30° C. for 30 minutes. The DNA was purified byadding Ampure XP beads to each plate. For the ESP and HGCP plates, 90 μLof Ampure XP beads were added. For the LRP plate, 50 μL of Ampure XPbeads were added. DNA was eluted with 17.5 μL of RSB.

12.5 μL of Illumina's ATL was added to the eluted DNA and transferred toa new plate. The plates with the eluted DNA were incubated at 37° C. for30 minutes.

Adapters were ligated to the DNA by adding 2.5 μL of RSB, 2.5 μL ofLigation (LIG) mix, and 2.5 μL of adapters to each well. The sampleswere mixed well and the plate was sealed. The plate was incubated for 10minutes at 30° C. 5 μL of STL (0.5M EDTA) was added to each well. Thesamples were mixed thoroughly. The adapter ligated DNA was purified byadding 42.5 μL of Ampure XP beads to each well. Ligated DNA was elutedwith 50 μL of RSB. The ligated DNA was purified by adding 50 μL ofAmpure beads and eluting the DNA with 20 μL of RSB. The Ampure beadpurification and elution was performed twice.

The ligated DNA was amplified by adding 25 μL of 2× kappa hifipolymerase and 5 μL of primer to each ligated DNA sample and by runninga PCR with 8 cycles. The amplified DNA was purified with 50 μL of Ampurebeads and the DNA was eluted with 30 μL of RSB. The amplified DNA fromthe three different sample preparations were used to prepare the ESP,HGCP, and LRP libraries.

The ESP, HGCP, and LRP libraries were validated by running each libraryon a DNA 1000 chip and quantifying with a BR Qubit assay.

Hybrization reactions were performed on the ESP, HGCP, and LRP samplesusing ESP, HGCP and LRP specific capture probes. 3 independenthybridization reactions were set up according to Table 2.

TABLE 2 pull down ESP HGCP LRP DNA library ESP HGCP LRP probe ESP HGCPLRP

Hybridization reactions were performed according to Agilent's standardSureSelect protocol.

Example 2. Two Independent Workflows for the Production of ESP, HGCP andLRP Libraries

This example provides two independent workflows for the preparation ofan Exome Supplement Plus (ESP), high GC content (HGCP) and specificenrichment pulldown (LRP) library from a single nucleic acid sample.

RSB (or 50 mM Sodium Acetate) was added to two different Covarismicrotubes containing 1 μg of genomic DNA (DNA) from a single sample toproduce 52.5 μL of total volume in each microtube. The microtubes weredesignated as ESP/HGCP and LRP. The gDNA in the microtube was shearedusing the Covaris settings in Table 3.

TABLE 3 Covaris settings ESP/HGCP LRP Duty factor:    20%    20%Cyc/burst: 200  200  Time (sec): 80 25 Peak Incident Power (W): 50 50Temp (*C): 20 20

The microtubes were spun down and 50 μL of the fragmented DNA weretransferred to PCR plates. 10 μL of RSB was added to each well. TheESP/HGCP sample plate was heated at 65° C. for 5 minutes. Or theESP/HGCP and LRP plates were not heated at 65° C. 40 μL ERP was added toeach sample plate by pipetting up and down to mix. The plates weresealed. The plates were incubated at 30° C. for 30 minutes. The DNA waspurified by adding Ampure XP beads to each plate. For the ESP and HGCPplates, 90 μL of Ampure XP beads were added. For the LRP plate, 50 μL ofAmpure XP beads were added. DNA was eluted with 17.5 μL of RSB.

12.5 μL of ATL was added to the eluted DNA. The plates with the elutedDNA were incubated at 37° C. for 30 minutes.

Adapters were ligated to the DNA by adding 2.5 μL of RSB, 2.5 μL ofLigation (LIG) mix, and 2.5 μL of adapters to each well. The sampleswere mixed well and the plate was sealed. The plate was incubated for 10minutes at 30° C. 5 μL of STL (0.5M EDTA) was added to each well. Thesamples were mixed thoroughly. The adapter ligated DNA was purified byadding 42.5 μL of Ampure XP beads to each well. Ligated DNA was elutedwith 50 μL of RSB. The ligated DNA was purified by adding 50 μL ofAmpure beads and eluting the DNA with 20 μL of RSB. The Ampure beadpurification and elution was performed twice.

The ligated DNA was amplified by adding 25 μL of 2× kappa hifipolymerase and 5 μL of primer to each ligated DNA sample and by runninga PCR with 8 cycles. The amplified DNA was purified with 50 μL of Ampurebeads and the DNA was eluted with 30 μL of RSB. The amplified DNA fromthe sample preparations were used to prepare the ESP, HGCP, and LRPlibraries.

The ESP, HGCP, and LRP libraries were validated by running each libraryon a DNA High-Sensitivity chip and quantifying with a BR Qubit assay.

Hybrization reactions were performed on the ESP, HGCP, and LRP samplesusing ESP, HGCP and LRP specific capture probes. 3 independenthybridization reactions were set up according to Table 4.

TABLE 4 pull down ESP HGCP LRP DNA library ESP/HGCP ESP/HGCP LRP probeESP HGCP LRP

Hybridization reactions were performed according to Agilent's standardSureSelect protocol.

Example 3. A Single Workflow for the Production of ESP, HGCP and LRPLibraries

This example provides a single workflow for the preparation of an ExomeSupplement Plus (ESP), high GC content (HGCP) and specific enrichmentpulldown (LRP) library from a single nucleic acid sample.

RSB (or 50 mM Sodium Acetate) was added to a Covaris microtubecontaining 3 μg of genomic DNA (DNA) from a single sample to produce52.5 μL of total volume. The gDNA in the microtube was sheared using theCovaris settings in Table 5.

TABLE 5 Covaris settings Duty factor:    20% Cyc/burst: 200  Time (sec):25 Peak Incident Power (W): 50 Temp (*C): 20

The microtubes were spun down and 50 μL of the fragmented DNA weretransferred to a single PCR plate. 10 μL of RSB was added to each well.The sample plate was heated at 65° C. for 5 minutes or were not heatedat 65° C. 40 μL ERP was added to each sample plate by pipetting up anddown to mix. The plates were sealed. The plate were incubated at 30° C.for 30 minutes. The DNA was purified by adding Ampure XP beads to eachplate. 90 μL of Ampure XP beads were added to the plates. The mixturewas incubated for 8 minutes at room temperature. The standard Ampureprotocol was performed. Beads were rehydrated in 20 μL of thawed RSB for2 minutes at room temperature. 17.5 μL of supernatant was transferred tonew wells in an Illumina's ALP plate.

12.5 μL of ATL was added to the eluted DNA. The ALP plates wereincubated at 37° C. for 30 minutes.

Adapters were ligated to the DNA by adding 2.5 μL of RSB, 2.5 μL ofLigation (LIG) mix, and 2.5 μL of adapters to each well. The sampleswere mixed well and the plate was sealed. The plate was incubated for 10minutes at 30° C. 5 μL of STL (0.5M EDTA) was added to each well. Thesamples were mixed thoroughly. The adapter ligated DNA was purified byadding 42.5 μL of Ampure XP beads to each well. Ligated DNA was elutedwith 100 μL of RSB. 50 μL of Ampure XP beads were added to the 100 μL ofligated DNA. The 150 μL of the supernatant was transferred to a newwell, leaving the Ampure XP bead bound DNA in the previous wells. DNAwas eluted from the Ampure XP beads by adding 20 μL of RSB, the elutedDNA is the LRP subset.

20 μL of Ampure beads were added to the 150 μL of supernatant. The DNAwas eluted in 100 μL of RSB. 60 μL of Ampure XP beads were added to the100 μL of DNA. The 160 μL of supernatant was transferred to a new well,leaving the Ampure XP bead bound DNA in the previous wells. DNA waseluted from the Ampure XP beads by adding 20 μL of RSB, the eluted DNAis the ESP/HGCP subset.

The LRP subset of DNA and the ESP/HGCP subset of DNA were amplified byadding 25 μL of 2× kappa hifi polymerase and 5 μL of primer to eachligated DNA sample and by running a PCR with 8 cycles. The amplified DNAwas purified with 50 μL of Ampure XP beads and the beads were rehydratedin 30 μL of RSB. The amplified DNA from the subsets were used to preparethe ESP, HGCP, and LRP libraries.

The ESP, HGCP, and LRP libraries were validated by running each libraryon a DNA High-Sensitivity chip and quantifying with a BR Qubit assay.

Hybrization reactions were performed on the ESP, HGCP, and LRP samplesusing ESP, HGCP and LRP specific capture probes. 3 independenthybridization reactions were set up according to Table 6.

TABLE 6 pull down ESP HGCP LRP DNA library ESP/HGCP ESP/HGCP LRP probeESP HGCP LRP

Hybridization reactions were performed according to Agilent's standardSureSelect protocol.

Example 4. Shear Time and Fragment Sizes

Genomic DNA (gDNA) was sheared by varying the shear time of a Covarissetting. The gDNA fragments produced by various shear times was thenanalyzed. Results are shown in FIG. 5 and Table 7.

TABLE 7 Shear time and mean fragment size Shear Time Mean FragmentNumber (seconds) Size (base pairs) 1 375 150 2 175 200 3 80 200 4 40 4005 32 500 6 25 800

Example 5. Bead Ratio and Fragment Size

The ratio of the volume of beads to the volume of the nucleic acidsample was varied and the effects of these ratios on mean fragment sizewas analyzed. As can be shown in FIG. 6A, varying the ratio of thevolume of the volume of the beads to the volume of the nucleic acidsample from 0.8 (line 1), 0.7 (line 2), 0.6 (line 3), 0.5 (line 4) and0.4 (line 5) resulted in a shift in the mean size of the DNA fragments.Generally, it appeared that the lower the ratio, then the larger themean fragment size.

Example 6. Ligation Reactions and Fragment Size

A combination of two different shear times and three different ligationreactions were conducted on a nucleic acid sample. Sample 1 was shearedfor 25 seconds and a ligation reaction was performed on the long insertDNA as prepared by Step 5 of Example 9 (lig-up). Sample 2 was shearedfor 32 seconds and a ligation reaction was performed on the long insertDNA as prepared by Step 5 of Example 9 (lig-up). Sample 3 was shearedfor 25 seconds and a ligation reaction was performed on the mid insertDNA as prepared by Step 8 of Example 9 (lig-mid). Sample 4 was shearedfor 32 seconds and a ligation reaction was performed on the mid insertDNA as prepared by Step 8 of Example 9 (lig-mid). Sample 5 was shearedfor 25 seconds and a ligation reaction was performed on the short insertDNA as prepared by Step 11 of Example 9 (lig-low). Sample 6 was shearedfor 32 seconds and a ligation reaction was performed on the short insertDNA as prepared by Step 11 of Example 9 (lig-low). FIG. 7 shows the meanfragment size for the six reactions.

Example 7. Rhodobacter sphaeroides

The Rhodobacter sphaeroides ATCC 17025 genome is 4.56 Million base pairslong and the GC content of the genome was analyzed. Results for theanalysis are shown in Table 8.

TABLE 8 Browser Chrom/ Length GC Gene NCBI RefSeq Plasmid Name (bp)Content (%) Count Accession chr 3217726 68.48 3181 NC_009428plasmid_pRSPA01 877879 67.69 849 NC_009429 plasmid_pRSPA02 289489 67.6278 NC_009430 plasmid_pRSPA03 121962 69.36 114 NC_009431 p1asmid_pRSPA0436198 64.05 32 NC_009432 plasmid_pRSPA05 13873 58.93 12 NC_009433

Example 8. Optimization of Rhodobacter sphaeroides DNA (High GC Content)

DNA from Rhodobacter sphaeroides was amplified with a variety ofpolymerases and amplification conditions. Amplified DNA was thensequenced. High GC flowcell refers to sequencing reactions on DNAsamples comprising primarily DNA with high GC content. Mix GC flowcellrefers to sequencing reactions on DNA samples comprising a mixture ofDNA with high and low GC content. As shown in Tables 9, brief heating at65° C. before ER (end repair) improved coverage of high GC content DNA(see PST-000292).

TABLE 9 2 × 150, High GC flowcell (primarily High GC content) ratio DNAPCR conditions PF reads mapped reads (>80% GC, <60% GC) PST-000190 PCRfree 985736 945734 95.94% 73.90% PST-000191 kapa 10 cycle 12119301174309 96.90% 70.80% PST-000192 kapa 10 cycle + betaine 1247310 120691796.76% 70.80% PST-000193 kapa 10 cycle + DMSO 1183084 1144464 96.74%70.40% PST-000194 kapa hifi 10 cycle 1102832 1067306 96.78% 68.30%PST-000195 kapa hifi 10 cycle + 756856 739857 97.75%  2.40% deaza_dGTPPST-000196 kapa GC 10 cycle 1299004 1255979 96.69% 70.60% PST-000197illumina 10 cycle 1347780 1298231 96.32% 52.10% PST-000198 illumina 10cycle, 1256278 1209607 96.28% 50.60% long denature PST-000199 kapa 8cycle 1013116 978349 96.57% 69.80% 2 × 150, Mix GC flowcell (high andlow GC content) PST-000191 kapa 10 cycle 909256 854341 93.96% 66.80% 2 ×250, Mix GC flowcell (high and low GC content) PST-000290 PCR free1009022 779191 77.22% 70.80% PST-000291 PCR free, 60C ER 1100298 86305878.44% 73.10% PST-000292 PCR free, 65C ER 1157944 932378 80.52% 78.20%PST-000293 PCR free, 70C ER 1200318 944391 78.68% 75.10%

Example 9. Preparation of Genomic DNA

The following steps were used to prepare subsets of nucleic acidmolecules from a sample comprising genomic DNA:

1. A sample comprising genomic DNA is sheared with M220 for 15-35seconds.

2. The fragmented gDNA was purified with SPRI beads after ligation(ratio of the volume of SPRI beads to the DNA sample was 1) and the DNAwas eluted into 100 μL of elution buffer (EB).

3. 50 μL of SPRI beads were added to the 100 μL of DNA.

4. The supernatant was transferred to a new tube.

5. The DNA from the remaining bead bound DNA was eluted. This eluted DNAwas called the long insert.

6. 10 μL of SPRI beads were added to the supernatant from Step 4.

7. The supernatant from Step 6 was transferred to a new tube.

8. The DNA from the remaining bead bound DNA of Step 6 was eluted. Thiseluted DNA was called the mid insert.

9. 20 μL of SPRI beads were added to the supernatant from Step 7.

10. The supernatant from Step 9 was transferred to a new tube.

11. The DNA from the remaining bead bound DNA of Step 9 was eluted. Thiseluted DNA was called the short insert.

Example 10. Segregation and Independent Processing of InterpretableGenomic Content

Illumina TruSeq Exome enrichment followed by Illumina sequencing is atypical example of targeted DNA sequencing. However, this process canfail to target many biomedically interesting non-exomic as well asexomic regions for enrichment and also can fail to adequately sequencemany of the regions it does target. Furthermore, many of the sequencedregions may have unacceptably high error rates. We found that many ofthese gaps and failures are due to specific problems that, whiledifficult for bulk sequencing, may be more adequately addressed byspecialized sequencing protocols or technologies.

We have compiled a large and unique set of medically interpretablecontent encompassing both proprietary data and numerous publiclyavailable sources that include both exomic and non-exomic regions, aswell as non-reference or alternative sequences. Much of this isn'tadequately covered in standard exome sequencing. We have analyzed thisperformance gap and developed a multipronged approach to more completelycover this content by independently processing particular types ofproblems with specialized sample preparation, amplification, sequencingtechnology and/or bioinformatics to best recover the underlyingsequence. We have developed three targeted subsets and protocols toaddress this performance gap.

In content regions skipped by standard exome processing but still innominally tractable genomic regions, we have developed additional baitsto enrich these regions for standard sequencing. In some cases, we mayadditionally target non-reference sequence that is of interest (e.g.common normal and/or cancer SV junctions, common InDels or in generalsequences in which the reference has a rare allele that we believe willadversely affect enrichment hybridization performance for most of thepopulation). This Exome Supplement Pulldown (ESP) can be pooled withstandard exome DNA libraries for very economical sequencing. Table 10lists proprietary and public data sets of medical and research interestas well as the anticipated coverage gap with Illumina's TruSeq exomekit. Table 10 shows an exemplary list of nucleic acid molecules in theESP subset.

TABLE 10 List of content in the ESP subset Missed in Missed inContent120924LG.bed by Set Cumulative TruSeq by Set TruSeq CumulativePriority Content Name Bases Ranges Bases Ranges Bases Ranges BasesRanges  1 MendelDB_snp_0913_2012.bed 78,882 1,576 65,968 1,163 13,844299 13,844 299  2 PharmGKB_snp_0914_2012.bed 14,600 292 80,253 1,4448,642 178 22,486 477  3 medical_dbSNP_regulome1_Suspect.bed 22,005 440100,522 1,836 15,796 323 38,088 794  4 GeneReview_snp_0913_2012.bed61,615 1,231 114,970 2,098 11,459 249 41,520 865  5HGMD_ClinVar_snp_0913_2012.bed 1,062,528 21,220 779,524 12,537 197,5943,873 219,612 4,313  6 Clinical_Channel_snp_0913_2012.bed 771,293 15,404928,410 15,103 219,084 4,239 324,542 6,309  7 OMIM_snp_0914_2012.bed500,554 9,999 928,410 15,103 102,540 2,092 324,542 6,309  8Varimed_multi_ethnic_snp_0914_2012.bed 89,201 1,784 1,002,730 16,56877,177 1,568 391,484 7,660  9 Varimed_highconf_snp_0914_2012.bed1,177,673 23,553 2,032,039 36,733 1,073,682 21,358 1,355,991 26,787 10HGMD_mut.bed 4,305,255 84,885 3,421,232 51,658 556,284 8,900 1,698,98031,491 11 Exons_VIP-Genes-120713 233,123 652 3,604,514 51,812 49,783 3311,738,877 31,691 12 Regulome1_VIP-Genes-120713 3,000 60 3,606,632 51,8502,503 54 1,740,885 31,732 13 Exons_MendelDB-Genes-120916 14,325,63340,761 16,091,103 71,703 3,726,418 19,767 5,049,919 45,516 14Regulome1_MendelDB-Genes-120916 147,553 2,951 16,201,606 73,825 125,1292,553 5,157,542 47,677 15 Exons_HGMD-Genes-120913 26,801,793 74,19529,292,835 105,150 7,047,052 36,440 8,633,799 64,224 16Regulome1_HGMD-Genes-120913 254,356 5,087 29,381,797 106,849 214,2864,372 8,720,429 65,963 17 Exons_CancerGeneCensus_gene 3,786,660 9,92431,022,066 110,788 934,846 4,641 9,113,184 67,842 18Regulome1_CancerGeneCensus_gene 31,651 633 31,031,990 110,976 27,842 5699,122,893 68,033 19 Exons_OMIM_Mendelian_gene 19,484,727 54,28532,499,571 114,516 5,032,796 26,346 9,518,418 69,854 20Regulome1_OMIM_Mendelian_gene 210,906 4,218 32,522,006 114,944 179,6853,668 9,540,226 70,290 21 Exons_HGMD_Mendelian_gene 27,988,755 77,42735,226,837 121,987 7,363,878 37,504 10,174,050 73,377 22Regulome1_HGMD_Mendelian_gene 266,255 5,325 35,260,944 122,647 226,9274,632 10,207,319 74,046 23 Exons_HLAclass1 5,969 24 35,260,944 122,6473,554 26 10,207,319 74,046 24 Regulome1_HLAclass1 950 19 35,260,944122,647 743 15 10,207,319 74,046 25 Exons_HLAclass2 28,398 82 35,273,022122,664 11,750 50 10,209,818 74,060 26 Regulome1_HLAclass2 350 735,273,098 122,665 100 2 10,209,868 74,061 27 CFTR_Intronic 603 335,273,651 122,667 603 3 10,210,421 74,063 28 Triallelic_in_Footprint7,891 154 35,280,947 122,809 7,434 150 10,217,712 74,205 29phastConsElements46way-top0.5percent 2,662,784 7,681 36,864,760 126,3521,794,961 5,994 11,753,993 78,509

In content regions having very high GC content (>70%), standardsequencing typically performs poorly because the elevated T_(m) (meltingtemperature) of these areas can cause poor PCR or other amplificationdue to competition with more numerous lower T_(m) sequences. Thesesequences are also enriched for other problem, e.g. hairpins and othersecondary structure. These regions are typically either skipped orperform poorly in standard sequencing. We have developed an enrichmentprocess to target content areas of high GC content (HGCP) and havedeveloped customized sample preparation and sequencing protocols tospecifically improve the performance of this library by optimizingtemperatures, incubation times, buffers and enzymes. An examplecomposition of such a library intersected with our content is shown inTable 11.

TABLE 11 Exemplary list of content in the HGCP subset Includes 50 bpdilation HGCPmerge100_1209241G.bed by Set Cumulative HGCP by Set HGCPCumulative Priority Content Name Bases Ranges Bases Ranges Bases RangesBases Ranges Mendel DB_snp_0913_2012.bed 180,101 909 180,101 909 12,53989 12,539 89 PharmGKB_snp_0914_2012.bed 42,673 266 222,474 1,173 3,09222 15,631 111 medical_dbSNP_regulome1_Suspect.bed 62,226 390 281,6291,547 883 7 16,387 116 GeneReview_snp_0913_2012.bed 143,233 753 322,1061,765 11,074 77 20,586 145 HGMD_ClinVar_snp_0913_2012.bed 1,881,4038,749 1,976,714 9,287 162,863 948 166,434 971Clinical_Channel_snp_0913_2012.bed 1,553,376 7,442 2,382,381 11,058112,701 674 185,369 1,075 OMIM_snp_0914_2012.bed 1,091,353 5,5272,382,381 11,058 92,276 563 185,369 1,075Varimed_multi_ethnic_snp_0914_2012.bed 269,869 1,600 2,609,304 12,3414,066 29 188,395 1,097 Varimed_highconf_snp_0914_2012.bed 3,538,00419,531 5,749,403 29,271 26,929 203 208,093 1,244 HGMD_mut.bed 4,713,06618,283 8,448,253 37,978 448,145 2,157 481,839 2,386Exons_VIP-Genes-120713 301,582 564 8,655,649 38,208 31,335 100 506,8732,445 Regulome1_VIP-Genes-120713 9,180 48 8,661,738 38,231 0 0 506,8732,445 Exons_MendelDB-Genes-120916 18,594,872 32,943 23,550,190 57,8021,986,487 6,270 2,147,437 7,091 Regulome1_MendelDB-Genes-120916 445,3602,606 23,890,795 59,262 9,488 77 2,151,072 7,110 Exons_HGMD-Genes-12091334,574,073 60,810 40,302,799 85,129 3,697,923 11,625 3,918,341 12,444Regulome1_HGMD-Genes-120913 765,607 4,447 40,572,922 86,302 14,220 1153,921,622 12,455 Exons_CancerGeneCensus_gene 4,823,472 8,240 42,627,24189,578 526,402 1,590 4,139,209 13,145 Regulome1_CancerGeneCensus_gene95,341 581 42,657,367 89,729 2,374 17 4,140,165 13,150Exons_OMIM_Mendelian_gene 25,166,172 44,269 44,497,746 92,630 2,702,6768,437 4,340,856 13,745 Regulome1_OMIM_Mendelian_gene 636,246 3,72644,567,099 92,943 14,171 111 4,342,155 13,751 Exons_HGMD_Mendelian_gene36,090,180 63,709 48,011,279 98,805 3,871,482 12,113 4,684,379 14,795Regulome1_HGMD_Mendelian_gene 802,747 4,700 48,116,355 99,290 17,080 1334,685,899 14,802 Exons_HLAclass1 8,432 9 48,116,355 99,290 3,128 34,685,899 14,802 Regulome1_HLAclass1 2,995 10 48,116,355 99,290 0 04,685,899 14,802 Exons_HLAclass2 38,082 65 48,130,838 99,292 1,017 64,686,134 14,804 Regulome1_HLAclass2 913 5 48,130,855 99,292 0 04,686,134 14,804 CFTR_Intronic 903 3 48,131,608 99,294 0 0 4,686,13414,804 Triallelic_in_Footprint 23,509 128 48,154,196 99,400 632 44,686,366 14,806 phastConsElements46way-top0.5percent 3,417,667 6,72850,091,253 102,331 162,245 531 4,721,759 14,903

Repetitive elements in the genome and other genomic regions outside ofthe exome can be difficult to sequence, align and/or assemble,particularly with short read technology (e.g. 2×100 on Illumina HiSeq).Many of these regions in the exome are skipped or perform poorly withstandard with standard enrichment strategies. Genomic regions outsidethe exome (such as introns of HLA) are typically not targeted by exomesequencing. The difficulties in sequencing may be due to poor enrichmentefficiency, degenerate mapping of reads and inadequate read length tospan common simple tandem repeats or biomedically relevant expandingrepeats. We addressed these problems by developing a specific enrichmentpulldown (LRP) and protocol to extract primarily these regions for moreexpensive long paired read sequencing (e.g. 2×250 bp on Illumina MiSeq)or long single read sequencing (e.g., 5 kb single molecule sequencing onPacBio RS or future technologies as available). This longer readsequencing technology is currently 10-fold to several 100-fold moreexpensive per base than bulk sequencing and is often not currentlycommercially viable for the entire content regions. Furthermore, in somecase (e.g. PacBio RS) the raw error profile is problematic for generaluse in SNV calling. However for some types of important problems itthese technologies are required for accurate or clinical quality resultsto correctly map degenerate sequence or span a repeat sequence. We havedeveloped a bulk protocol in which all such regions separated into asubset and are sequenced in parallel to achieve a useful economy ofscale for the preparation yet still limit the total amount of sequencingto a practical amount. In addition to sequencing this with a differenttechnology, we have customized our alignment and other bioinformaticpipeline elements to best leverage these longer reads to improvecoverage, accuracy and characterization (e.g. allelotyping STRS andunstable expanding repeat regions). Phasing and/or haplotyping of HLAand blood typing genes is more tractable using longer reads and longermolecules provided in this library. Reassembly of ambiguous regions ismore tractable using the longer molecules and reads from theselibraries. An example composition of such a library is listed in Table12. In addition the intersection of this library with particular classesof problem or genomic content is shown in the final block.

TABLE 12 Includes 100 bp dilation LRPmerge300_1209241G.bed by SetCumulative LRP by Set LRP Cumulative Priority Content Name Bases RangesBases Ranges Bases Ranges Bases Ranges MendelDB_snp_0913_2012.bed300,380 823 300,380 823 83,107 238 83,107 238 PharmGKB_snp_0914_2012.bed71,926 258 372,876 1,076 17,087 65 100,722 302medical_dbSNP_regulome1_Suspect.bed 107,508 371 474,890 1,433 77,284 267173,712 560 GeneReview_snp_0913_2012.bed 239,363 690 542,080 1,63572,372 210 194,354 624 HGMD_ClinVar_snp_0913_2012.bed 3,074,892 7,7743,241,005 8,261 945,906 2,543 1,022,992 2,782Clinical_Channel_snp_0913_2012.bed 2,537,774 6,684 3,880,310 9,829723,269 2,045 1,162,383 3,154 OMIM_snp_0914_2012.bed 1,811,109 5,0193,880,310 9,829 554,960 1,605 1,162,383 3,154Varimed_multi_ethnic_snp_0914_2012.bed 484,477 1,439 4,295,467 10,934153,156 419 1,299,826 3,485 Varimed_highconf_snp_0914_2012.bed 6,365,50216,815 9,980,716 25,215 1,574,979 3,476 2,671,355 6,283 HGMD_mut.bed7,400,636 15,605 14,095,445 32,199 2,199,289 4,999 3,861,157 8,525Exons_VIP-Genes-120713 387,447 472 14,341,711 32,377 147,978 1943,958,330 8,621 Regulome1_VIP-Genes-120713 15,830 41 14,353,492 32,3875,972 14 3,962,756 8,624 Exons_MendelDB-Genes-120916 23,887,624 26,91332,552,166 47,917 7,780,357 11,130 10,049,097 16,057Regulome1_MendelDB-Genes-120916 794,991 2,347 33,211,287 48,852 150,309470 10,133,001 16,215 Exons_HGMD-Genes-120913 44,321,062 49,86653,983,227 69,498 14,883,355 21,110 17,258,590 25,544Regulome1_HGMD-Genes-120913 1,355,456 4,013 54,494,848 70,283 266,188794 17,324,858 25,670 Exons_CancerGeneCensus_gene 6,121,488 6,82657,070,263 72,967 2,045,184 2,809 18,218,353 26,867Regulome1_CancerGeneCensus_gene 173,742 520 57,133,995 73,058 27,135 9418,229,400 26,886 Exons_OMIM_Mendelian_gene 32,224,942 36,331 59,444,38775,405 10,505,055 15,008 18,976,117 27,934 Regulome1_OMIM_Mendelian_gene1,129,215 3,368 59,571,025 75,634 191,633 620 18,989,192 27,963Exons_HGMD_Mendelian_gene 46,253,280 52,403 63,975,577 80,407 15,161,05921,685 20,193,619 29,734 Regulome1_HGMD_Mendelian_gene 1,416,254 4,27364,173,958 80,756 248,193 810 20,221,296 29,790 Exons_HLAclass1 10,894 364,173,958 80,756 10,894 3 20,221,296 29,790 Regulome1_HLAclass1 5,912 664,173,958 80,756 5,912 6 20,221,296 29,790 Exons_HLAclass2 50,951 4264,188,111 80,758 50,951 42 20,235,449 29,792 Regulome1_HLAclass2 2,1963 64,188,111 80,758 2,196 3 20,235,449 29,792 CFTR_Intronic 1,203 364,189,624 80,759 0 0 20,235,449 29,792 Triallelic_in_Footprint 39,060117 64,232,417 80,836 36,957 109 20,276,075 29,864phastConsElements46way-top0.5percent 4,269,414 6,189 66,642,340 83,2431,011,328 1,857 20,709,245 30,497 HLA-ClassI 22,744 3 66,651,185 83,23822,744 3 20,718,090 30,492 HLA-ClassII 140,811 10 66,728,362 83,207140,811 10 20,795,267 30,461 BloodTypingf10k 206,568 3 66,902,785 83,169206,568 3 20,972,246 30,428 AmylaseRegion 300,200 1 67,200,752 83,169300,200 1 21,271,226 30,427 ImportantCompressions 192,112 3 67,379,34083,156 192,112 3 21,449,546 30,416 SMN1_SMN2 57,657 2 67,428,632 83,14657,657 2 21,498,838 30,406 by Set Cumulative LRP by Set LRP CumulativePriority Problem Name Bases Ranges Bases Ranges Bases Ranges BasesRanges v3NoCoverage 51,511,046 26,632 51,506,246 26,608 756,946 947756,946 947 ShortPEReadMappabilty 131,941,961 31,071 135,610,684 40,8981,415,767 1,581 1,445,847 1,660 SingleReadMappabilty 239,094,172 149,523241,428,271 156,194 2,364,928 3,258 2,382,194 3,311ValidatedCompressions 3,262,543 36 244,073,867 155,934 54,267 712,427,518 3,363 SegmentalDuplications 162,351,720 6,902 287,784,823145,772 4,084,205 4,129 4,393,421 4,945 STR > 50 bp 128,885,115 201,050395,004,522 297,226 1,209,546 2,883 5,359,052 7,494 GRCh37patches61,247,019 134 433,409,533 292,018 3,302,921 3,265 7,821,274 9,930v3LowCoverage 746,244,957 683,267 966,704,005 689,651 15,671,569 25,81220,709,245 30,497 HLA-ClassI 22,744 3 966,704,005 689,651 22,744 320,718,090 30,492 HLA-ClassII 140,811 10 966,704,005 689,651 140,811 1020,795,267 30,461 BloodTypingf10k 206,568 3 966,723,788 689,642 206,5683 20,972,246 30,428 AmylaseRegion 300,200 1 966,815,712 689,618 300,2001 21,271,226 30,427 ImportantCompressions 192,112 3 966,817,041 689,617192,112 3 21,449,546 30,416 SMN1_SMN2 57,657 2 966,817,041 689,61757,657 2 21,498,838 30,406

We have developed all three of these libraries and have preliminary datacombining standard TruSeq Exome and ESP to produce what we call Exome+,Extended Exome or ACE (Accuracy and Content Enhanced) Exome (Tables13-14). This significantly improves coverage of the RefSeq exons, ourcustomized Exome as well as dramatic improvement on customized Variants(as many of these are outside the exome).

TABLE 13 Whole Exome Extended Exome Whole Genome (E+, ESP) Full FlowcellTruSeqExome (Alpha demo (PL 2.0) (PL 2.0) B in P1) A Product CategoryPersonalis Personalis Personalis Description of Product Type Set Size92× 54× 56× comparison metrics ~Price Point Size Unit A B A B A B A BNEMAR corrections Bronze NEMAR.DegappedGenome 1,102 kbp 765,476 64,32425,409 3,170 31,894 3,522 Homozygous Homozygous Genome NEMAR.RefSeqExons17.999 kbp 12,488 1,059 10,436 1,045 11,224 1,046 major allele minorallele NEMAR.RefSeqCodingExons 6.692 kbp 4,713 383 4,460 419 4,573 393‘variants’ variants NEMAR.RefSeqUTR 11.307 kbp 7,775 676 5,976 626 6,651653 removed called NEMAR.PersonalisExome 7.394 kbp 5,029 435 4,356 4464,915 468 NEMAR.PersonalisVariants 4.050 kbp 2,171 360 376 72 1,851 371NEMAR.PersonalisNetContent 11.080 kbp 7,005 769 4,547 489 6,573 812Reference DegappedGenome 2,861 Mbp 98.7% 51  3.7% 50  5.1% 49 Coverage %of Error: −10log10 RefSeqExons 70,487 kbp 98.7% 52 77.9% 49 88.1% 48target reported (#Errors/ RefSeqCodingExons 33,366 kbp 99.0% 53 85.4% 4994.7% 48 (GC > 50, not SetSize) RefSeqUTR 37,101 kbp 98.4% 52 69.1% 5080.3% 48 LowQual) (1-Specificity) PersonalisExome 29,056 kbp 99.2% 5381.3% 49 94.2% 48 (GQ > 50, not PersonalisVariants 172 kbp 99.8% 4983.0% 49 96.0% 47 LowQual) PersonalisNetContent 29,095 kbp 99.3% 5380.0% 49 93.9% 48 Conten.RefSegFirstCodingExons 2,389 kbp 99.1% 53 74.0%47 89.0% 48 Content.GCgt70 1,639 kbp 99.0% 53 38.2% 48 65.6% 47Content.NoMapPEO 903 kbp 71.0% 46 54.0% 38 61.1% 36Content.Segmental_Duplications 2,046 kbp 89.1% 43 71.9% 38 77.5% 37Content.HomopolymerFlank 136 kbp 97.2% 44 57.7% 41 77.3% 37Content.STRgt50f50 453 kbp 94.0% 42 66.8% 34 77.2% 33 SNPsDegappedGenome 2,861 Mbp 95.3% 0.34%  1.9%  1.65%  3.0% 1.26% Coverage:% Error: % RefSeqExons 70,467 kbp 95.8% 0.21% 61.9%  1.60% 76.6% 1.46%of target Discordance/ RefSeqCodingExons 33,366 kbp 95.0% 0.19% 69.7% 1.61% 85.4% 1.50% reported VariantLoci RefSeqUTR 37,101 kbp 96.3% 0.22%57.2%  1.60% 71.3% 1.44% (GQ > 50, not (1-Sensitivity) PersonalisExome29,056 kbp 95.6% 0.21% 64.0%  1.50% 83.3% 1.30% LowQual) (GQ > 50, notPersonalisVariants 172 kbp 99.8% 0.02% 12.6%  0.31% 72.7% 0.10% LowQual)PersonalisNetContent 29,095 kbp 97.0% 0.14% 44.1%  1.44% 79.1% 0.93%Content.RefSegFirstCodingExons 2,389 kbp 92.8% 0.10% 60.5%  1.17% 76.5%0.74% Content.GCgt70 1,639 kbp 91.2% 0.11% 24.3%  1.21% 47.9% 0.82%Content.NoMapPEO 903 kbp 65.4% 1.06% 46.3% 10.98% 56.1% 8.72%Content.Segmental_Duplications 2,046 kbp 83.6% 0.97% 56.2%  7.00% 65.0%7.01% Content.HomopolymerFlank 138 kbp 81.8% 1.28% 23.1% 13.64% 50.3%7.64% Content.STRgt50f50 453 kbp 76.6% 1.29% 59.1%  9.90% 68.1% 9.94%

TABLE 14 Reference Loci Variant Loci All Loci Genomic HQ Phred HQ ErrorHQ Phred Region Library Cov Error Cov % Cov Error Region DefinitionRefSeq TruSeq 79.6% 49 64.0% 1.55% 78.6% 46 All exons and UTRs Exome+88.1% 48 76.6% 1.46% 87.3% 46 Interpretable TruSeq 83.2% 49 65.8% 1.43%82.3% 47 46 PharmGKB VIP genes Exome Exome+ 94.2% 48 83.3% 1.30% 93.6%46 1,803 MendelDB genes 3,502 HGMD genes 488 Cancer genes 2,896 OMIMMendelian genes 3,493 HGMD Mendelian genes (90-95% of symbols covered inESP v1) Interpretable TruSeq 85.2% 46 13.3% 0.24% 78.6% 43 MendelDB SNPVariants Exome+ 96.0% 47 72.7% 0.10% 93.9% 41 PharmGKB SNP Medical dbSNPRegulome1 suspect GeneReview SNP HGMD Clinvar SNP Clinical Channel SNPOMIM SNP Varimed Multiethnic SNP Varimed High Confidence SNP

It should be understood from the foregoing that, while particularimplementations have been illustrated and described, variousmodifications may be made thereto and are contemplated herein. Anembodiment of one aspect of the disclosure may be combined with ormodified by an embodiment of another aspect of the disclosure. It is notintended that the invention(s) be limited by the specific examplesprovided within the specification. While the invention(s) has (or have)been described with reference to the aforementioned specification, thedescriptions and illustrations of embodiments of the invention(s) hereinare not meant to be construed in a limiting sense. Furthermore, it shallbe understood that all aspects of the invention(s) are not limited tothe specific depictions, configurations or relative proportions setforth herein which depend upon a variety of conditions and variables.Various modifications in form and detail of the embodiments of theinvention(s) will be apparent to a person skilled in the art. It istherefore contemplated that the invention(s) shall also cover any suchmodifications, variations and equivalents.

What is claimed is:
 1. A method of analyzing a nucleic acid sampleisolated from a biological sample of an individual to detect a presenceor an absence of cancer, comprising (a) contacting said nucleic acidsample with one or more capture probe sets to produce one or morecapture probe hybridized nucleic acid molecules, wherein said one ormore capture probe sets are configured to selectively enrich for anexome; (b) conducting one or more sequencing reactions on said one ormore capture probe hybridized nucleic acid molecules to produce one ormore sequencing reads; (c) analyzing said one or more sequencing reads,with the aid of a computer processor, to produce a unified assessment ofa genetic state of said nucleic acid sample at each locus addressed bysaid sequencing reaction; and (d) generating a biomedical report thatincludes biomedical information of said subject, which biomedicalinformation is indicative of said genetic state.
 2. The method of claim1, wherein said biomedical information of said subject is predictive,prognostic, or diagnostic of one or more biomedical features selectedfrom the group consisting of disease state, genetic risk of disease,efficacy of a drug therapy, and prediction of optimal drug dosage. 3.The method of claim 1, wherein said biological sample of said subject isselected from the group consisting of: tissue, cell, skin, blood,plasma, serum, saliva, sputum, semen, transvaginal fluid, cerebrospinalfluid, and any combination thereof.
 4. The method of claim 3, whereinsaid tissue is selected from the group consisting of: malignant tissue,benign tissue, or a combination thereof.
 5. The method of claim 3,wherein said bodily fluid is plasma.
 6. The method of claim 1, whereinsaid one or more capture probe sets are conjugated to beads.
 7. Themethod of claim 1, wherein said one or more capture probe sets furthercomprise barcodes.
 8. The method of claim 1, wherein said exomecomprises: (a) exons, (b) untranslated regions (UTRs), and (c) one ormore splice sites, one or more intronic regions, one or more regulatoryregions, or a combination thereof.
 9. The method of claim 8, whereinsaid one or more regulatory regions comprise regulatory regionsidentified in a Regulome database.
 10. The method of claim 8, whereinsaid one or more regulatory regions comprise non-coding regulatoryregions.
 11. The method of claim 10, wherein said non-coding regulatoryregions comprise regulatory elements located in 5′ or 3′ untranslatedregions.
 12. The method of claim 10, wherein said non-coding regulatoryregions comprise regulatory elements located within introns.
 13. Themethod of claim 1, further comprising contacting said nucleic acidsample with one or more additional sets of capture probes, wherein saidone or more additional capture probe sets is configured to selectivelyenrich for genomic region features.
 14. The method of claim 13, whereinsaid genomic region features comprises one or more sets of genes withbiomedically interpretable variants.
 15. The method of claim 14, whereinsaid biomedically interpretable variants comprise a polymorphism in agene that is associated with cancer.
 16. The method of claim 1, whereinsaid nucleic acid sample comprises DNA, RNA, or cDNA derived from RNA.17. The method of claim 1, wherein said sequencing reaction produces atleast 250,000,000 sequencing reads.
 18. The method of claim 1, whereinsaid sequencing reaction produces at least 500,000,000 sequencing reads.19. The method of claim 1, wherein said sequencing reaction produces atleast 750,000,000 sequencing reads.
 20. The method of claim 1, whereinsaid sequencing reaction produces at least 1,000,000,000 sequencingreads.